Crawler Report for docs.nvidia.com

Summary

Website Quality Score

5.6 Fair
Performance
9.5
SEO
3.5
Security
6.5
Accessibility
3.5
Best Practices
4.2
  • ⛔ Skipped URLs - 1142 skipped URLs found.
  • ⛔ Redirects - 21 redirects found.
  • ⛔ 404 CRITICAL - 9 non-existent pages found.
  • ⛔ 14 page(s) with multiple <h1> headings.
  • ⛔ 3 page(s) without lang attribute.
  • ⛔ Security - 7134 pages(s) with critical finding(s).
  • ⚠️ The description '' exceeds the allowed 10% duplicity. 96% of pages have this same description.
  • ⚠️ 3565 page(s) do not support Brotli compression.
  • ⚠️ No WebP image found on the website.
  • ⚠️ No AVIF image found on the website.
  • ⚠️ 15 page(s) with large inline SVGs (> 5120 bytes).
  • ⚠️ 6 page(s) with duplicated inline SVGs (> 5 duplicates).
  • ⚠️ 5 page(s) with deep DOM (> 30 levels).
  • ⚠️ 7 page(s) with non-clickable (non-interactive) phone numbers.
  • ⚠️ 24 page(s) without image alt attributes.
  • ⚠️ 3530 page(s) without form labels.
  • ⚠️ 3562 page(s) without aria labels.
  • ⚠️ 3530 page(s) without role attributes.
  • ⏩ Loaded robots.txt for domain 'docs.nvidia.com': status code 200, size 3 kB and took 134 ms.
  • ⏩ External URLs - 1142 external URL(s) found.
  • ⏩ DNS IPv6: domain docs.nvidia.com does not support IPv6 (DNS server: 127.0.0.53).
  • ✅ SSL/TLS certificate is valid until Jan 22 23:59:59 2027 GMT. Issued by C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1. Subject is C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com.
  • ✅ SSL/TLS certificate issued by 'C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1'.
  • ✅ Performance OK - all non-media URLs are faster than 3 seconds.
  • ✅ HTTP headers - found 27 unique headers.
  • ✅ All 2685 unique title(s) are within the allowed 10% duplicity. Highest duplicity title has 0%.
  • ✅ All pages have quoted attributes.
  • ✅ All pages have valid or none inline SVGs.
  • ✅ All pages have <h1> heading.
  • ✅ All pages have heading structure without skipped levels.
  • ✅ All pages have valid HTML.
  • ✅ DNS IPv4 OK: domain docs.nvidia.com resolved to docs.nvidia.com.edgekey.net., e33907.a.akamaiedge.net., 80.239.150.75, 80.239.150.72, 80.239.150.91, 80.239.150.8, 80.239.150.59, 80.239.150.80, 80.239.150.35, 80.239.150.17, 80.239.150.96 (DNS server: 127.0.0.53).
  • 📌 DNS Aliases: IP(s) for domain docs.nvidia.com were resolved by CNAME chain docs.nvidia.com > docs.nvidia.com.edgekey.net > e33907.a.akamaiedge.net.

Visited URLs

Found 3595 row(s).
URLStatusTypeTime (s)SizeCache
/nemo301 Redirect21 ms 123 B0 s
/nemo/200 HTML74 ms 137 kB0 s
/nemo/%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20…0%20%20%20%20%20%20%20%20301 Redirect34 ms 355 B0 s
/nemo/curator/latest/200 HTML171 ms85 kB0 s
/nemo-framework/user-guide/latest/overview.html200 HTML53 ms 45 kB0 s
/nemo/automodel/latest/index.html200 HTML49 ms 66 kB0 s
/nemo/run/latest/200 HTML404 ms21 kB0 s
/nemo/rl/latest/index.html200 HTML23 ms 65 kB0 s
/nemo/microservices/latest/200 HTML81 ms 116 kB0 s
/nemo/index.html200 HTML22 ms 137 kB0 s
/nemo/megatron-bridge/latest/200 HTML430 ms95 kB0 s
/nemo/agent-toolkit/latest/index.html200 HTML35 ms 188 kB0 s
/nemo/guardrails/latest/200 HTML64 ms 57 kB0 s
/nemo/retriever/latest/200 HTML422 ms50 kB0 s
/nemo/export-deploy/latest/index.html200 HTML430 ms89 kB0 s
/nemo/gym/latest/index.html200 HTML70 ms 66 kB0 s
/nemo/evaluator/latest/200 HTML170 ms75 kB0 s
/nemo-framework/user-guide/latest/index.html301 Redirect57 ms 205 B0 s
/nemo-framework/user-guide/latest/speech_ai/index.html200 HTML67 ms 44 kB0 s
/nemo/megatron-bridge/latest/index.html200 HTML22 ms 95 kB0 s
/nemo-framework/user-guide/latest/speech_ai/magpietts.html200 HTML56 ms 62 kB0 s
/nemo/run/latest/index.html200 HTML21 ms 21 kB0 s
/nemo-framework/user-guide/latest/speech_ai/magpietts-longform.html200 HTML68 ms 60 kB0 s
/nemo-framework/user-guide/latest/speech_ai/magpietts-po.html200 HTML543 ms71 kB0 s
/nemo/evaluator/latest/index.html200 HTML23 ms 75 kB0 s
/nemo-framework/user-guide/latest/softwarecomponentversions.html200 HTML49 ms 54 kB0 s
/nemo/curator/latest/index.html200 HTML23 ms 85 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/apis.html200 HTML544 ms37 kB0 s
/nemo-framework/user-guide/latest/playbooks/index.html200 HTML64 ms 54 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/index.html200 HTML199 ms39 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/collections.html200 HTML468 ms37 kB0 s
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/nemo-framework/user-guide/latest/libraries/index.html200 HTML90 ms 40 kB0 s
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/nemo/automodel/latest/about/index.html200 HTML53 ms 46 kB0 s
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/nemo/automodel/latest/guides/overview.html200 HTML659 ms45 kB0 s
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/nemo/automodel/latest/guides/huggingface-api-compatibility.html200 HTML93 ms 50 kB0 s
/nemo/automodel/latest/guides/gradient-checkpointing.html200 HTML401 ms43 kB0 s
/nemo/automodel/latest/repository-structure.html200 HTML580 ms47 kB0 s
/nemo/automodel/latest/model-coverage/vlm.html200 HTML453 ms50 kB0 s
/nemo/automodel/latest/launcher/local-workstation.html200 HTML576 ms48 kB0 s
/nemo/automodel/latest/guides/fp8-training.html200 HTML534 ms49 kB0 s
/nemo/automodel/latest/launcher/cluster.html200 HTML414 ms60 kB0 s
/nemo/automodel/latest/model-coverage/troubleshooting.html200 HTML534 ms38 kB0 s
/nemo/automodel/latest/model-coverage/llm.html200 HTML445 ms76 kB0 s
/nemo/automodel/latest/model-coverage/diffusion.html200 HTML444 ms39 kB0 s
/nemo/automodel/latest/guides/mlflow-logging.html200 HTML558 ms58 kB0 s
/nemo/automodel/latest/guides/checkpointing.html200 HTML416 ms67 kB0 s
/nemo/automodel/latest/guides/quantization-aware-training.html200 HTML534 ms65 kB0 s
/nemo/automodel/latest/announcements.html200 HTML408 ms34 kB0 s
/nemo/automodel/latest/guides/configuration.html200 HTML446 ms51 kB0 s
/nemo/automodel/latest/guides/dataset-overview.html200 HTML758 ms113 kB0 s
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/nemo/automodel/latest/about/key-features.html200 HTML543 ms58 kB0 s
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/nemo/automodel/latest/model-coverage/overview.html200 HTML568 ms40 kB0 s
/nemo/rl/latest/guides/environments.html200 HTML532 ms65 kB0 s
/nemo/rl/latest/fp8.html200 HTML519 ms51 kB0 s
/nemo/rl/latest/model-quirks.html200 HTML522 ms48 kB0 s
/nemo/rl/latest/design-docs/chat-datasets.html200 HTML395 ms49 kB0 s
/nemo/rl/latest/guides/dtensor-tp-accuracy.html200 HTML444 ms74 kB0 s
/nemo/rl/latest/about/quick-start.html200 HTML391 ms44 kB0 s
/nemo/rl/latest/about/installation.html200 HTML402 ms50 kB0 s
/nemo/rl/latest/design-docs/env-vars.html200 HTML422 ms46 kB0 s
/nemo/rl/latest/about/overview.html200 HTML498 ms43 kB0 s
/nemo/rl/latest/guides/dpo.html200 HTML392 ms61 kB0 s
/nemo/rl/latest/about/evaluation.html200 HTML537 ms46 kB0 s
/nemo/rl/latest/design-docs/padding.html200 HTML421 ms53 kB0 s
/nemo/rl/latest/about/performance-summary.html200 HTML385 ms56 kB0 s
/nemo/rl/latest/guides/grpo-deepscaler.html200 HTML43 ms 48 kB0 s
/nemo/rl/latest/debugging.html200 HTML480 ms50 kB0 s
/nemo/rl/latest/design-docs/training-backends.html200 HTML529 ms51 kB0 s
/nemo/rl/latest/design-docs/generation.html200 HTML427 ms71 kB0 s
/nemo/rl/latest/testing.html200 HTML756 ms60 kB0 s
/nemo/rl/latest/local-workstation.html200 HTML408 ms45 kB0 s
/nemo/rl/latest/design-docs/design-and-philosophy.html200 HTML533 ms58 kB0 s
/nemo/rl/latest/design-docs/checkpointing.html200 HTML58 ms 46 kB0 s
/nemo/rl/latest/design-docs/dependency-management.html200 HTML638 ms77 kB0 s
/nemo/rl/latest/adding-new-models.html200 HTML506 ms82 kB0 s
/nemo/rl/latest/design-docs/fsdp2-parallel-plan.html200 HTML693 ms45 kB0 s
/nemo/rl/latest/guides/sft.html200 HTML444 ms85 kB0 s
/nemo/rl/latest/design-docs/sequence-packing-and-dynamic-batching.html200 HTML400 ms87 kB0 s
/nemo/rl/latest/design-docs/logger.html200 HTML596 ms59 kB0 s
/nemo/rl/latest/guides/dapo.html200 HTML502 ms59 kB0 s
/nemo/rl/latest/nsys-profiling.html200 HTML53 ms 62 kB0 s
/nemo/rl/latest/guides/eval.html200 HTML408 ms57 kB0 s
/nemo/rl/latest/guides/sft-openmathinstruct2.html200 HTML534 ms54 kB0 s
/nemo/rl/latest/documentation.html200 HTML510 ms49 kB0 s
/nemo/rl/latest/guides/use-custom-vllm.html200 HTML397 ms58 kB0 s
/nemo/rl/latest/design-docs/loss-functions.html200 HTML531 ms52 kB0 s
/nemo/rl/latest/apidocs/index.html200 HTML427 ms69 kB0 s
/nemo/rl/latest/about/clusters.html200 HTML587 ms41 kB0 s
/nemo/rl/latest/about/backends.html200 HTML407 ms43 kB0 s
/nemo/rl/latest/design-docs/uv.html200 HTML404 ms53 kB0 s
/nemo/rl/latest/guides/grpo.html200 HTML406 ms91 kB0 s
/nemo/rl/latest/cluster.html200 HTML387 ms60 kB0 s
/nemo/rl/latest/about/tips-and-tricks.html200 HTML515 ms45 kB0 s
/nemo/rl/latest/guides/async-grpo.html200 HTML394 ms63 kB0 s
/nemo/rl/latest/about/model-support.html200 HTML397 ms44 kB0 s
/nemo/rl/latest/guides/grpo-sliding-puzzle.html200 HTML454 ms82 kB0 s
/nemo/microservices/latest/requirements.html200 HTML79 ms 96 kB0 s
/nemo/rl/latest/docker.html200 HTML414 ms48 kB0 s
/nemo/rl/latest/guides/rm.html200 HTML542 ms64 kB0 s
/nemo/rl/latest/guides/deepseek.html200 HTML403 ms43 kB0 s
/nemo/rl/latest/about/features.html200 HTML372 ms44 kB0 s
/nemo/megatron-bridge/latest/recipe-usage.html200 HTML435 ms89 kB0 s
/nemo/megatron-bridge/latest/megatron-lm-to-megatron-bridge.html200 HTML439 ms144 kB0 s
/nemo/microservices/latest/eula.html200 HTML697 ms79 kB0 s
/nemo/megatron-bridge/latest/nemo2-migration-guide.html200 HTML467 ms280 kB0 s
/nemo/megatron-bridge/latest/skills-index.html200 HTML451 ms58 kB0 s
/nemo/megatron-bridge/latest/performance-guide.html200 HTML389 ms143 kB0 s
/nemo/megatron-bridge/latest/bridge-rl-integration.html200 HTML469 ms129 kB0 s
/nemo/megatron-bridge/latest/README.html200 HTML411 ms102 kB0 s
/nemo/megatron-bridge/latest/adding-new-models.html200 HTML459 ms93 kB0 s
/nemo/megatron-bridge/latest/parallelisms.html200 HTML86 ms 114 kB0 s
/nemo/megatron-bridge/latest/performance-summary.html200 HTML415 ms117 kB0 s
/nemo/agent-toolkit/latest/run-workflows/launching-ui.html200 HTML40 ms 190 kB0 s
/nemo/megatron-bridge/latest/bridge-tech-details.html200 HTML505 ms102 kB0 s
/nemo/megatron-bridge/latest/documentation.html200 HTML409 ms69 kB0 s
/nemo/agent-toolkit/latest/run-workflows/mcp-server.html200 HTML87 ms 213 kB0 s
/nemo/megatron-bridge/latest/bridge-guide.html200 HTML414 ms98 kB0 s
/nemo/agent-toolkit/latest/build-workflows/a2a-client.html200 HTML388 ms205 kB0 s
/nemo/agent-toolkit/latest/build-workflows/about-building-workflows.html200 HTML152 ms188 kB0 s
/nemo/agent-toolkit/latest/resources/migration-guide.html200 HTML440 ms232 kB0 s
/nemo/agent-toolkit/latest/run-workflows/a2a-server.html200 HTML451 ms201 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/sizing-calc.html200 HTML436 ms217 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/test-time-compute.html200 HTML418 ms201 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/optimizer.html200 HTML806 ms286 kB0 s
/nemo/agent-toolkit/latest/resources/troubleshooting.html200 HTML781 ms182 kB0 s
/nemo/agent-toolkit/latest/run-workflows/fastmcp-server.html200 HTML485 ms199 kB0 s
/nemo/agent-toolkit/latest/build-workflows/workflow-configuration.html200 HTML80 ms 208 kB0 s
/nemo/agent-toolkit/latest/extend/plugins.html200 HTML748 ms206 kB0 s
/nemo/agent-toolkit/latest/build-workflows/embedders.html200 HTML78 ms 191 kB0 s
/nemo/agent-toolkit/latest/build-workflows/mcp-client.html200 HTML57 ms 233 kB0 s
/nemo/agent-toolkit/latest/get-started/installation.html200 HTML109 ms199 kB0 s
/nemo/agent-toolkit/latest/build-workflows/retrievers.html200 HTML481 ms200 kB0 s
/nemo/agent-toolkit/latest/components/sharing-components.html200 HTML886 ms195 kB0 s
/nemo/agent-toolkit/latest/run-workflows/about-running-workflows.html200 HTML420 ms196 kB0 s
/nemo/agent-toolkit/latest/resources/security-considerations.html200 HTML1.1 s 189 kB0 s
/nemo/agent-toolkit/latest/resources/support.html200 HTML42 ms 177 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/evaluate.html200 HTML85 ms 338 kB0 s
/nemo/agent-toolkit/latest/resources/faq.html200 HTML470 ms180 kB0 s
/nemo/agent-toolkit/latest/get-started/quick-start.html200 HTML100 ms185 kB0 s
/nemo/agent-toolkit/latest/reference/cli.html200 HTML828 ms294 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/profiler.html200 HTML497 ms260 kB0 s
/nemo/agent-toolkit/latest/release-notes.html200 HTML118 ms178 kB0 s
/nemo/agent-toolkit/latest/build-workflows/memory.html200 HTML100 ms188 kB0 s
/nemo/agent-toolkit/latest/api/index.html200 HTML870 ms295 kB0 s
/nemo/retriever/200 HTML91 ms 115 kB0 s
/nemo/agent-toolkit/latest/build-workflows/object-store.html200 HTML451 ms200 kB0 s
/nemo/agent-toolkit/latest/improve-workflows/about-improving-workflows.html200 HTML431 ms179 kB0 s
/nemo/guardrails/latest/troubleshooting.html200 HTML568 ms48 kB0 s
/nemo/export-deploy/latest/apidocs/index.html200 HTML522 ms49 kB0 s
/nemo/export-deploy/latest/llm/index.html200 HTML584 ms40 kB0 s
/nemo/export-deploy/latest/documentation.html200 HTML504 ms38 kB0 s
/nemo/gym/latest/training-tutorials/index.html200 HTML108 ms46 kB0 s
/nemo/export-deploy/latest/testing.html200 HTML538 ms37 kB0 s
/nemo/gym/latest/about/index.html200 HTML53 ms 36 kB0 s
/nemo/export-deploy/latest/mm/index.html200 HTML533 ms39 kB0 s
/nemo/gym/latest/environment-tutorials/multi-step-environment.html200 HTML578 ms55 kB0 s
/nemo/gym/latest/infrastructure/index.html200 HTML64 ms 35 kB0 s
/nemo/gym/latest/model-recipes/nemotron-3-nano.html200 HTML323 ms76 kB0 s
/nemo/gym/latest/data/prepare-validate.html200 HTML656 ms82 kB0 s
/nemo/gym/latest/about/ecosystem.html200 HTML52 ms 38 kB0 s
/nemo/gym/latest/environment-tutorials/real-world-environment.html200 HTML720 ms35 kB0 s
/nemo/gym/latest/get-started/index.html200 HTML437 ms45 kB0 s
/nemo/gym/latest/data/index.html200 HTML52 ms 61 kB0 s
/nemo/gym/latest/training-tutorials/multi-environment-training.html200 HTML509 ms37 kB0 s
/nemo/gym/latest/environment-tutorials/index.html200 HTML550 ms46 kB0 s
/nemo/gym/latest/training-tutorials/unsloth.html200 HTML63 ms 34 kB0 s
/nemo/gym/latest/apidocs/index.html200 HTML523 ms36 kB0 s
/nemo/gym/latest/environment-tutorials/adding-a-benchmark.html200 HTML528 ms37 kB0 s
/nemo/gym/latest/environment-tutorials/designing-customer-evaluation.html200 HTML525 ms36 kB0 s
/nemo/gym/latest/infrastructure/deployment-topology.html200 HTML555 ms48 kB0 s
/nemo/gym/latest/troubleshooting/configuration.html200 HTML41 ms 41 kB0 s
/nemo/gym/latest/model-server/vllm.html200 HTML528 ms53 kB0 s
/nemo/gym/latest/get-started/detailed-setup.html200 HTML77 ms 68 kB0 s
/nemo/gym/latest/training-tutorials/offline-training-w-rollouts.html200 HTML409 ms85 kB0 s
/nemo/gym/latest/contribute/development-setup.html200 HTML583 ms51 kB0 s
/nemo/gym/latest/reference/faq.html200 HTML45 ms 96 kB0 s
/nemo/gym/latest/reference/rl-framework-compatibility.html200 HTML538 ms35 kB0 s
/nemo/gym/latest/model-server/index.html200 HTML41 ms 36 kB0 s
/nemo/gym/latest/model-recipes/nemotron-3-super.html200 HTML419 ms32 kB0 s
/nemo/gym/latest/reference/cli-commands.html200 HTML629 ms91 kB0 s
/nemo/gym/latest/agent-server/index.html200 HTML74 ms 40 kB0 s
/nemo/gym/latest/contribute/index.html200 HTML545 ms42 kB0 s
/nemo/gym/latest/get-started/rollout-collection.html200 HTML45 ms 52 kB0 s
/nemo/gym/latest/model-recipes/index.html200 HTML588 ms36 kB0 s
/nemo/gym/latest/environment-tutorials/real-world-implementation.html200 HTML411 ms60 kB0 s
/nemo/gym/latest/environment-tutorials/integrate-external-environments.html200 HTML573 ms42 kB0 s
/nemo/gym/latest/environment-tutorials/single-step-environment.html200 HTML191 ms119 kB0 s
/nemo/gym/latest/environment-tutorials/stateful-environment.html200 HTML89 ms 52 kB0 s
/nemo/gym/latest/resources-server/index.html200 HTML515 ms40 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/examples/kinyarwanda_asr.html200 HTML64 ms 122 kB0 s
/nemo/gym/latest/data/download-huggingface.html200 HTML613 ms65 kB0 s
/nemo/gym/latest/reference/configuration.html200 HTML447 ms55 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/ssl/resources.html200 HTML77 ms 37 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/all_chkpt.html200 HTML61 ms 91 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…iarization/resources.html200 HTML52 ms 37 kB0 s
/nemo/gym/latest/environment-tutorials/real-world-data-generation.html200 HTML478 ms36 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tts/datasets.html200 HTML45 ms 67 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tts/magpietts-longform.html200 HTML42 ms 55 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/speech_intent_slot/models.html200 HTML45 ms 36 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…_recognition/results.html200 HTML105 ms52 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tools/speech_data_explorer.html200 HTML46 ms 48 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/ssl/configs.html200 HTML623 ms91 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…_recognition/configs.html200 HTML74 ms 48 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/ssl/datasets.html200 HTML46 ms 36 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tools/speech_data_processor.html200 HTML86 ms 36 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…diarization/datasets.html200 HTML66 ms 65 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/common/metrics.html200 HTML536 ms35 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/checkpoints/intro.html200 HTML436 ms43 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tools/intro.html200 HTML147 ms36 kB0 s
/nemo-framework/user-guide/latest/model-optimization/s…culative/speculative.html200 HTML80 ms 42 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/speaker_recognition/intro.html200 HTML47 ms 43 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/speech_intent_slot/intro.html200 HTML408 ms40 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spee…_intent_slot/configs.html200 HTML240 ms59 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tools/nemo_forced_aligner.html200 HTML62 ms 67 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tts/magpietts.html200 HTML44 ms 61 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/features/parallelisms.html301 Redirect22 ms 203 B0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spee…assification/results.html200 HTML528 ms53 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…ecognition/resources.html200 HTML456 ms37 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/speech_intent_slot/api.html200 HTML89 ms 37 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/features/optimizations/index.html200 HTML121 ms36 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/core/neural_types.html200 HTML52 ms 64 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/core/api.html200 HTML389 ms156 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/starthere/intro.html200 HTML44 ms 47 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tts/configs.html200 HTML437 ms72 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/tools/ctc_segmentation.html200 HTML88 ms 38 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/speechlm2/intro.html200 HTML437 ms57 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/asr/spea…r_diarization/models.html200 HTML76 ms 58 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/core/adapters/components.html200 HTML401 ms59 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/speechlm2/models.html200 HTML53 ms 56 kB0 s
/nemo-framework/user-guide/latest/nemotoolkit/core/adapters/api.html200 HTML534 ms56 kB0 s
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/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…apper/register/index.html200 HTML236 ms198 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…timizer/prompt/index.html200 HTML506 ms187 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…ction_tracking/index.html200 HTML808 ms204 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/cli/re…ng/red_teaming/index.html200 HTML854 ms189 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…o_agent/prompt/index.html200 HTML480 ms190 kB0 s
/nemo/agent-toolkit/latest/api/nat/cli/commands/config…channel/remove/index.html200 HTML152 ms186 kB0 s
/nemo/agent-toolkit/latest/api/observability/processor…/nim_converter/index.html200 HTML715 ms192 kB0 s
/nemo/guardrails/latest/configure-rails/nemoguardrails/colang/v2_x/library/404 HTML742 ms77 kB0 s
/nemo/guardrails/nemoguardrails/colang/v2_x/library301 Redirect85 ms 215 B0 s
/nemo/guardrails/nemoguardrails/llm/prompts301 Redirect26 ms 199 B0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…callback_class/index.html200 HTML797 ms179 kB0 s
/nemo/guardrails/examples/v2_x/tutorial/hello_world_1301 Redirect41 ms 219 B0 s
/nemo/guardrails/latest/configure-rails/examples/v2_x/tutorial/hello_world_1/404 HTML506 ms77 kB0 s
/nemo/guardrails/latest/configure-rails/nemoguardrails/llm/prompts/404 HTML828 ms77 kB0 s
/nemo/guardrails301 Redirect73 ms 145 B0 s
/nemo/guardrails/0.15.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML483 ms35 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…atest/support-matrix.html200 HTML56 ms 27 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest301 Redirect23 ms 237 B0 s
/nemo/guardrails/0.18.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML398 ms35 kB0 s
/nemo/guardrails/0.17.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML376 ms36 kB0 s
/nemo/guardrails/0.16.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML533 ms35 kB0 s
/nemo/guardrails/0.14.1/user-guides/advanced/jailbreak-detection-deployment.html200 HTML520 ms33 kB0 s
/nemo/guardrails/0.14.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML506 ms33 kB0 s
/nemo/guardrails/0.19.0/user-guides/advanced/jailbreak-detection-deployment.html200 HTML434 ms35 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…t_agent/prompt/index.html200 HTML409 ms184 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…/model_trainer/index.html200 HTML815 ms190 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/c…er_agent/agent/index.html200 HTML781 ms209 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…c/calculations/index.html200 HTML787 ms198 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…on/data_models/index.html200 HTML766 ms316 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…prompt_caching/index.html200 HTML840 ms190 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…oo_agent/agent/index.html200 HTML467 ms236 kB0 s
/nemo/agent-toolkit/latest/api/nat/cli/commands/config…hannel/channel/index.html200 HTML421 ms186 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…_wrapper/agent/index.html200 HTML774 ms208 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…mework_wrapper/index.html200 HTML760 ms194 kB0 s
/nemo/guardrails/nemoguardrails/colang/v2_x/library/404 HTML531 ms77 kB0 s
/nemo/guardrails/examples/v2_x/tutorial/hello_world_1/404 HTML381 ms77 kB0 s
/nemo/guardrails/nemoguardrails/llm/prompts/404 HTML528 ms77 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/reference.html200 HTML434 ms18 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/air-gapped.html200 HTML430 ms27 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…latest/release-notes.html200 HTML64 ms 19 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…test/troubleshooting.html200 HTML405 ms17 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…latest/configuration.html200 HTML633 ms29 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…test/prompt-template.html200 HTML522 ms24 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…integrate-guardrails.html200 HTML47 ms 18 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/performance.html200 HTML462 ms22 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…latest/observability.html200 HTML44 ms 32 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/index.html200 HTML537 ms23 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/200 HTML199 ms23 kB0 s
/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v…test/getting-started.html200 HTML554 ms59 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…stack_analysis/index.html200 HTML75 ms 188 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…casting/config/index.html200 HTML393 ms183 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…/output_parser/index.html200 HTML770 ms208 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…dynamo_metrics/index.html200 HTML418 ms289 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…on/llm_metrics/index.html200 HTML419 ms187 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…lc/calc_runner/index.html200 HTML864 ms222 kB0 s
/nemo/agent-toolkit/latest/api/nat/cli/commands/configure/channel/add/index.html200 HTML883 ms186 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…stack_analysis/index.html200 HTML798 ms210 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…eneck_analysis/index.html200 HTML774 ms181 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…n/experimental/index.html200 HTML781 ms181 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/langchain/a…ct_agent/agent/index.html200 HTML937 ms217 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…_span_analysis/index.html200 HTML829 ms226 kB0 s
/nemo/agent-toolkit/latest/api/nat/plugins/eval/profil…spike_analysis/index.html200 HTML786 ms223 kB0 s
No rows found, please edit your search term.

Best practices

Found 11 row(s).
Analysis nameOKNoticeWarningCritical
Heading structure70223014
Duplicate inline SVGs (> 5 and > 1024 B)155020
Non-clickable phone numbers30120
Invalid inline SVGs156000
DOM depth (> 30)3569041
Large inline SVGs (> 5120 B)154020
Title uniqueness (> 10%)2685000
Description uniqueness (> 10%)121010
Brotli support0035650
WebP support0010
AVIF support0010
No rows found, please edit your search term.

Large inline SVGs

SeverityOccursDetailAffected URLs (max 5)
warning15<svg xmlns="http://www.w3.org/2000/svg" style="display:none" id="iconsMap"> ...URL 1, URL 2, URL 3, URL 4, URL 5

Duplicate inline SVGs

SeverityOccursDetailAffected URLs (max 5)
warning36x SVG (1140 B): <svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-mortar-board sd-mr-1" viewBox="0 0 24 24" aria-hidden="true"> ...URL 1, URL 2, URL 3
warning17x SVG (1140 B): <svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-mortar-board sd-mr-1" viewBox="0 0 24 24" aria-hidden="true"> .../nemo/microservices/latest/guardrails/tutorials/index.html
warning17x SVG (1047 B): <svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-apps sd-mr-1" viewBox="0 0 16 16" aria-hidden="true"> .../nemo/microservices/latest/about/key-features.html
warning19x SVG (1140 B): <svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-mortar-board sd-mr-1" viewBox="0 0 24 24" aria-hidden="true"> .../nemo/microservices/latest/fine-tune/tutorials/index.html

Invalid inline SVGs

No problems found.


Missing quotes on attributes

No problems found.


DOM depth

SeverityOccursDetailAffected URLs (max 5)
critical1The DOM depth exceeds the critical limit: 50. Found depth: 51./nemo/megatron-bridge/0.1.0/apidocs/brid…a.datasets.sft.html
warning1The DOM depth exceeds the warning limit: 30. Found depth: 33./nemo/microservices/latest/fine-tune/man…spec-reference.html
warning1The DOM depth exceeds the warning limit: 30. Found depth: 35./nemo/microservices/latest/fine-tune/man…obs/create-job.html
warning1The DOM depth exceeds the warning limit: 30. Found depth: 36./nemo/microservices/latest/fine-tune/man…nfig-reference.html
warning1The DOM depth exceeds the warning limit: 30. Found depth: 40./nemo/microservices/latest/evaluate/eval…/target-schema.html

Heading structure

SeverityOccursDetailAffected URLs (max 5)
critical26Multiple <h1> headings found.URL 1, URL 2, URL 3, URL 4, URL 5
notice12No headings found in the HTML content.URL 1, URL 2, URL 3, URL 4, URL 5

Non-clickable phone numbers

Found 12 row(s).
SeverityOccursDetailAffected URLs (max 5)
warning24111-1111-1111URL 1, URL 2
warning2555-123-4567URL 1, URL 2
warning2(555) 123-4567URL 1, URL 2
warning1+------------------/nemo/automodel/latest/_modules/nemo_aut…s/capabilities.html
warning1+1-800-555-0199/nemo/microservices/latest/generate-priv…orted-entities.html
warning1+---------/nemo/rl/latest/guides/grpo-sliding-puzzle.html
warning1800-555-0199/nemo/microservices/latest/generate-priv…orted-entities.html
warning1+--------------------/nemo/gym/latest/environment-tutorials/m…ep-environment.html
warning1+----------------/nemo/automodel/latest/_modules/nemo_aut…s/capabilities.html
warning1+------------/nemo/rl/latest/design-docs/sequence-pac…namic-batching.html
warning1555-123-4568/nemo/microservices/latest/generate-priv…orted-entities.html
warning1(800) 555-0123/nemo/microservices/latest/generate-priv…egex-detection.html
No rows found, please edit your search term.

Title uniqueness

No problems found.


Description uniqueness

No problems found.

Accessibility

Analysis nameOKNoticeWarningCritical
Missing image alt attributes3810150
Missing aria labels180527375
Missing roles00270
Missing html lang attribute1001
Missing form labels0070

Valid HTML

No problems found.


Missing image alt attributes

SeverityOccursDetailAffected URLs (max 5)
warning300<img ***>URL 1, URL 2, URL 3, URL 4, URL 5

Missing form labels

SeverityOccursDetailAffected URLs (max 5)
warning3523<input class="form-*" name="q" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning19<input class="task-*" *** >URL 1, URL 2, URL 3
warning12<input name="term" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning1<input class="md-*" name="query" *** >/nemo/retriever/latest/

Missing aria labels

Found 56 row(s).
SeverityOccursDetailAffected URLs (max 5)
critical1418<input id="sd-tab-item-***" name="sd-tab-set-***" *** >URL 1, URL 2, URL 3, URL 4, URL 5
critical19<input class="task-*" *** >URL 1, URL 2, URL 3
critical12<input name="term" *** >URL 1, URL 2, URL 3, URL 4, URL 5
critical5<input class="md-* md-* md-*" id="__nav_1_2_***" *** >/nemo/retriever/latest/
critical1<input class="md-* md-*" id="__nav_***" *** >/nemo/retriever/latest/
critical1<input class="md-*" id="__drawer" *** >/nemo/retriever/latest/
critical1<input class="md-*" id="__search" *** >/nemo/retriever/latest/
critical1<input class="md-* md-*" id="__nav_1_***" *** >/nemo/retriever/latest/
critical1<input class="md-* md-* md-*" id="__nav_1_***" *** >/nemo/retriever/latest/
warning1271462<a class="reference internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning39124<a class="headerlink" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning34689<a class="reference internal nav-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning25724<a class="external" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning16901<a class="reference external" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning7046<a class="navbar-* logo" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning6354<a class="nav-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning5034<a ***>URL 1, URL 2, URL 3, URL 4, URL 5
warning4480<a class="nav-* pst-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<a class="footer-* logo" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<button class="btn rounded-*" id="pst-back-to-top" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3393<a class="right-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3386<a class="left-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3326<a class="current reference internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning1040<a class="sd-* sd-* reference internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning560<a id="openPopupButton" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning465<a class="viewcode-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning234<a class="reference download internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning192<a class="NavigationLink" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning164<a class="reference internal image-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning153<button class="defcon3 accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning139<button class="defcon5 accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning134<a class="Link" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning97<button class="defcon4 accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning92<a class="external reference" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning52<a class="github reference external" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning49<a class="toc-*" *** >URL 1, URL 2, URL 3, URL 4
warning49<a class="reference internal" id="id***" *** >URL 1, URL 2, URL 3, URL 4
warning42<a class="md-*" *** >/nemo/retriever/latest/
warning27<a class="sd-* sd-* sd-* sd-* reference internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning26<a class="footnote-* brackets" id="id***" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning25<a class="sd-* sd-* reference external" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning24<button class="defcon2 accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning18<a class="Tabs-*" *** >URL 1, URL 2, URL 3, URL 4
warning14<button class="accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning12<a class="sd-* sd-* sd-* sd-* sd-* sd-* reference internal" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning8<button class="defcon1 accordion">URL 1, URL 2, URL 3, URL 4, URL 5
warning6<button class="Page-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning6<a class="sd-* sd-* sd-* sd-* sd-* reference external" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning6<a class="Page-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning6<a class="sd-* sd-* sd-* sd-* sd-* reference internal" *** >URL 1, URL 2, URL 3, URL 4
warning4<a class="sd-* sd-* sd-* sd-* reference external" *** >URL 1, URL 2
warning3<a class="bg-* reference internal image-*" *** >URL 1, URL 2
warning2<a class="Button" *** >URL 1, URL 2
warning1<a class="md-* md-*" *** >/nemo/retriever/latest/
warning1<a class="sd-* reference internal image-*" *** >/nemo/guardrails/latest/reference/guardr…uence-diagrams.html
warning1<button class="md-* md-*" *** >/nemo/retriever/latest/
No rows found, please edit your search term.

Missing roles

Found 20 row(s).
SeverityOccursDetailAffected URLs (max 5)
warning7046<footer class="bd-*">URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<footer class="prev-* d-*">URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<aside class="d-* d-*" id="bd-header-version-warning" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<header class="bd-* navbar navbar-* bd-* d-*">URL 1, URL 2, URL 3, URL 4, URL 5
warning3523<nav class="bd-* bd-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3491<nav class="d-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning3055<nav class="bd-* page-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning18<nav class="Navigation">URL 1, URL 2, URL 3, URL 4, URL 5
warning12<aside class="footnote-* brackets">URL 1, URL 2, URL 3, URL 4, URL 5
warning11<nav class="md-*" *** >/nemo/retriever/latest/
warning6<main class="Page-*" *** >URL 1, URL 2, URL 3, URL 4, URL 5
warning6<nav class="FooterNavigation">URL 1, URL 2, URL 3, URL 4, URL 5
warning6<footer class="Page-*">URL 1, URL 2, URL 3, URL 4, URL 5
warning4<nav class="contents local" id="tutorial-steps">URL 1, URL 2, URL 3, URL 4
warning3<nav class="md-* md-*" *** >/nemo/retriever/latest/
warning1<nav class="md-* md-* md-*" *** >/nemo/retriever/latest/
warning1<header class="md-*" *** >/nemo/retriever/latest/
warning1<footer class="md-*">/nemo/retriever/latest/
warning1<main class="md-*" *** >/nemo/retriever/latest/
warning1<aside class="md-* md-*">/nemo/retriever/latest/
No rows found, please edit your search term.

Missing html lang attribute

SeverityOccursDetailAffected URLs (max 5)
critical3HTML lang attribute is not present.URL 1, URL 2, URL 3

Security

Found 11 row(s).
HeaderOKNoticeWarningCriticalRecommendation
Strict-Transport-Security6003567Strict-Transport-Security header is not set. It enforces secure connections and protects against MITM attacks.
Server0603567Server header is set to 'istio-envoy'. It is better not to reveal used technologies.. Server header is set to 'AmazonS3'. It is better not to reveal the technologies used and especially their versions.
X-Frame-Options0035730X-Frame-Options header is not set. It prevents clickjacking attacks when set to 'deny' or 'sameorigin.
X-Content-Type-Options0035730X-Content-Type-Options header is not set. It stops MIME type sniffing and mitigates content type attacks.
Referrer-Policy0035730Referrer-Policy header is not set. It controls referrer header sharing and enhances privacy and security.
Feature-Policy0035730Feature-Policy header is not set. It allows enabling/disabling browser APIs and features for security. Not important if Permissions-Policy is set.
Permissions-Policy0035730Permissions-Policy header is not set. It allows enabling/disabling browser APIs and features for security.
X-Powered-By0060X-Powered-By header is set to 'Brightspot'. It is better not to reveal used technologies.
Set-Cookie0035730
X-XSS-Protection3573000
Content-Security-Policy3573000
No rows found, please edit your search term.

Security headers

Found 11 row(s).
SeverityOccursDetailAffected URLs (max 5)
critical3567Strict-Transport-Security header is not set. It enforces secure connections and protects against MITM attacks.URL 1, URL 2, URL 3, URL 4, URL 5
critical3567Server header is set to 'AmazonS***'. It is better not to reveal the technologies used and especially their versions.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573Feature-Policy header is not set. It allows enabling/disabling browser APIs and features for security. Not important if Permissions-Policy is set.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573X-Content-Type-Options header is not set. It stops MIME type sniffing and mitigates content type attacks.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573Referrer-Policy header is not set. It controls referrer header sharing and enhances privacy and security.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573X-Frame-Options header is not set. It prevents clickjacking attacks when set to 'deny' or 'sameorigin.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573Permissions-Policy header is not set. It allows enabling/disabling browser APIs and features for security.URL 1, URL 2, URL 3, URL 4, URL 5
warning3573Set-Cookie header for 'c_code' does not have 'HttpOnly' flag. Attacker can steal the cookie using XSS. Consider using 'HttpOnly' when cookie is not used by JavaScript.URL 1, URL 2, URL 3, URL 4, URL 5
warning6X-Powered-By header is set to 'Brightspot'. It is better not to reveal used technologies.URL 1, URL 2, URL 3, URL 4, URL 5
notice3573Set-Cookie header for 'c_code' does not have 'SameSite' flag. Consider using 'SameSite=Strict' or 'SameSite=Lax'.URL 1, URL 2, URL 3, URL 4, URL 5
notice6Server header is set to 'istio-envoy'. It is better not to reveal used technologies.URL 1, URL 2, URL 3, URL 4, URL 5
No rows found, please edit your search term.

TOP non-unique titles

Found 10 row(s).
Count 🔽Title
21Getting Started &#8212; NVIDIA NeMo Guardrails
14Input Rails &#8212; NVIDIA NeMo Guardrails
14Hello World &#8212; NVIDIA NeMo Guardrails
12Configuration Guide &#8212; NVIDIA NeMo Guardrails
10Observe Workflows &#8212; NVIDIA NeMo Agent Toolkit (1.5)
9Models &#8212; NVIDIA NeMo Framework User Guide
9Checkpoints &#8212; NVIDIA NeMo Framework User Guide
8garak report: /home/lderczynski/garak_results/abc_with_general_instructions.report.jsonl
8garak report: abc_with_general_instructions_and_dialog_rails.report.jsonl
8Datasets &#8212; NVIDIA NeMo Framework User Guide
No rows found, please edit your search term.

TOP non-unique descriptions

Count 🔽Description
3439
2NeMo Curator is an open-source, scalable data curation platform for curating large datasets across text, image, video, and audio modalities to improve AI model training
2NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
2NVIDIA NeMo Retriever (NeMo Retriever) is a collection of microservices that present a single API for indexing and querying of user data.<br/><br/>NeMo Retriever uses specialized NVIDIA NIM microservices to find, contextualize, and extract text, tables, and images that you can use in downstream generative applications.
2NVIDIA NeMo is a modular software suite of APIs and libraries that help developers manage the AI agent lifecycle—building, deploying, and optimizing AI agents at scale.
2Comprehensive overview of NeMo Curator

SEO metadata

Found 200 row(s).
URL 🔼IndexingTitleH1DescriptionKeywords
/dgx-cloud/run-ai/latest/nemo-e2e-example.htmlAllowed4. NeMo End-to-End Workflow Example — NVIDIA Run:ai on DGX Cloud Documentation4. NeMo End-to-End Workflow Example#
/nemo-framework/user-guide/latest/changelog.htmlAllowedChangelog — NVIDIA NeMo Framework User GuideChangelog#
/nemo-framework/user-guide/latest/knownissues.htmlAllowedKnown Issues — NVIDIA NeMo Framework User GuideKnown Issues#
/nemo-framework/user-guide/latest/libraries/index.htmlAllowedLibrary Documentation — NVIDIA NeMo Framework User GuideLibrary Documentation#
/nemo-framework/user-guide/latest/model-optimization/distillation/distillation.htmlAllowedDistillation — NVIDIA NeMo Framework User GuideDistillation#
/nemo-framework/user-guide/latest/model-optimization/pruning/pruning.htmlAllowedPruning — NVIDIA NeMo Framework User GuidePruning#
/nemo-framework/user-guide/latest/model-optimization/quantization/quantization.htmlAllowedQuantization — NVIDIA NeMo Framework User GuideQuantization#
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/nemo-guardrails/NVIDIA NeMo GuardrailsNeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.NVIDIA NeMo GuardrailsNeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
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/nemo/NVIDIA NeMoNVIDIA NeMo is a modular software suite of APIs and libraries that help developers manage the AI agent lifecycle—building, deploying, and optimizing AI agents at scale.NVIDIA NeMoNVIDIA NeMo is a modular software suite of APIs and libraries that help developers manage the AI agent lifecycle—building, deploying, and optimizing AI agents at scale.
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  • <h1> FAQ#
  • <h1> How To: Upload and download a dataset from HuggingFace#
    • <h2> Uploading with Pull Request workflow#
    • <h2> Deleting Datasets from Gitlab#
    • <h2> Downloading Datasets from Huggingface#
  • <h1> How To: Prepare and validate data for PR submission or RL training#
  • <h1> How To: Profile your resources server#
  • <h1> How To: Use Ray for parallelizing CPU-intensive tasks#
    • <h2> Ray Setup in NeMo Gym#
      • <h3> Automatic Initialization#
      • <h3> Ray Configuration#
    • <h2> Using Ray for CPU-Intensive Tasks#
  • <h1> FAQ: SFT and RL#
  • <h1> FAQ: PermissionError when starting NeMo Gym in sandboxed environments#
  • <h1> FAQ: build-docs / Build docs CI failures#
  • <h1> FAQ: Monotonic (Strictly-Increasing) Trajectories#
    • <h2> Recommended Approaches#
  • <h1> FAQ: Model responses from inference.nvidia.com have no diversity#
1810/nemo/gym/latest/reference/faq.html
  • <h1> Recipes and End-to-End Examples#
  • <h1> Large Language Models (LLM)#
    • <h2> Fine-Tuning#
    • <h2> Pretraining#
    • <h2> Knowledge Distillation (KD)#
    • <h2> Benchmark Configurations#
  • <h1> Vision Language Models (VLM)#
    • <h2> Fine-Tuning#
    • <h2> Generation#
  • <h1> Diffusion Models (Text-to-Image & Text-to-Video)#
    • <h2> Fine-Tuning#
    • <h2> Pretraining#
    • <h2> Generation#
    • <h2> Dataset Preparation#
144/nemo/automodel/latest/guides/overview.html
  • <h1> End-to-End Speaker Diarization Configuration Files#
    • <h2> Hydra Configurations for Sortformer Diarizer Training#
    • <h2> Hydra Configurations for Streaming Sortformer Diarizer Training#
    • <h2> Hydra Configurations for (Streaming) Sortformer Diarization Post-processing#
  • <h1> Cascaded Speaker Diarization Configuration Files#
    • <h2> Hydra Configurations for Diarization Training#
      • <h3> General Diarizer Configuration#
      • <h3> Dataset Configuration#
      • <h3> Pre-processor Configuration#
      • <h3> Model Architecture Configurations#
      • <h3> Loss Configurations#
  • <h1> Hydra Configurations for Diarization Inference#
    • <h2> Diarizer Configurations#
      • <h3> Configurations for Voice Activity Detector#
      • <h3> Configurations for Speaker Embedding in Diarization#
      • <h3> Configurations for Clustering in Diarization#
      • <h3> Configurations for Diarization with ASR#
173/nemo-framework/user-guide/latest/nemotoolkit/asr/speaker_diarization/configs.html
  • <h1> Checkpoints#
  • <h1> End-to-end Speaker Diarization Models#
    • <h2> Sortformer Diarizer Training#
    • <h2> Sortformer Diarizer Inference with Post-processing#
    • <h2> Streaming Sortformer Diarizer Training#
    • <h2> Streaming Sortformer Diarizer Inference with Post-processing#
    • <h2> HuggingFace Pretrained Checkpoints#
    • <h2> End-to-end Speaker Diarization Models#
  • <h1> Models for Cascaded Speaker Diarization Pipeline#
    • <h2> Loading Local Checkpoints#
    • <h2> Inference#
    • <h2> NGC Pretrained Checkpoints#
    • <h2> Models for Speaker Diarization Pipeline#
133/nemo-framework/user-guide/latest/nemotoolkit/asr/speaker_diarization/results.html
  • <h1> Add New Models#
    • <h2> Importance of Log Probability Consistency in Training and Inference#
    • <h2> Understand Discrepancies Between Backends#
    • <h2> 1. Hugging Face–Based Models#
      • <h3> Validation Workflow#
    • <h2> 2. Megatron Models#
      • <h3> Additional Validation#
    • <h2> 3. Expected Error Threshold#
  • <h1> Model Diagnostics#
    • <h2> 1.max_model_len_respected.py#
    • <h2> 2.long_generation_decode_vs_prefill#
    • <h2> 3.check_hf_model_embeddings_untrained.py#
    • <h2> 4.vllm_precision_compilation_test.py#
132/nemo/rl/latest/adding-new-models.html
  • <h1> Adapter Components#
  • <h1> Functional Form - Adapter Networks#
    • <h2> Insertion Form - Module Adapters#
    • <h2> Composition Function - Adapter Strategies#
    • <h2> References#
52/nemo-framework/user-guide/latest/nemotoolkit/core/adapters/components.html
  • <h1> Text-to-Speech (TTS)#
  • <h1> Resources and Documentation#
22/nemo-framework/user-guide/latest/nemotoolkit/tts/intro.html
  • <h1> Scores#
    • <h2> EN#
    • <h2> BE#
    • <h2> BY#
    • <h2> CA#
    • <h2> DE#
    • <h2> ENES#
    • <h2> EO#
    • <h2> ES#
    • <h2> FR#
    • <h2> HR#
    • <h2> IT#
    • <h2> KAB#
    • <h2> NL#
    • <h2> PL#
    • <h2> RU#
    • <h2> RW#
    • <h2> UA#
    • <h2> ZH#
  • <h1> Scores with Punctuation and Capitalization#
    • <h2> EN with P&C#
    • <h2> BY with P&C#
    • <h2> DE with P&C#
    • <h2> ES with P&C#
    • <h2> HR with P&C#
    • <h2> IT with P&C#
    • <h2> NL with P&C#
    • <h2> PL with P&C#
    • <h2> UA with P&C#
292/nemo-framework/user-guide/latest/nemotoolkit/asr/scores.html
  • <h1> Speech and Audio Processing#
  • <h1> Resources and Documentation#
22/nemo-framework/user-guide/latest/nemotoolkit/audio/intro.html
  • <h1> Viewing Audit Job Results#
    • <h2> About Audit Job Results#
    • <h2> Getting the List of Result Files#
    • <h2> Get an HTML Report#
  • <h1> garak run: garak.report.jsonl
    • <h2> config details
    • <h2> Results:
      • <h3> probe: dan.AutoDANCached - min. 100.0%
      • <h3> probe: goodside.Tag - min. 100.0%
    • <h2> Get the Report JSONL Log#
    • <h2> Get the Hitlog#
112/nemo/microservices/latest/audit/results.html
  • <h1> Running a Simple Audit Job in Docker#
    • <h2> Prerequisites#
    • <h2> Procedure#
  • <h1> garak run: garak.report.jsonl
    • <h2> config details
    • <h2> Results: nim.NVOpenAIChat / deepseek-ai/deepseek-r1-distill-llama-8b
      • <h3> probe: dan.AutoDANCached - min. 61.9%
      • <h3> probe: goodside.Tag - min. 100.0%
82/nemo/microservices/latest/audit/tutorials/get-started-docker.html
  • <h1> Auditing a Local NIM in Docker#
    • <h2> Prerequisites#
    • <h2> Procedure#
  • <h1> garak run: garak.report.jsonl
    • <h2> config details
    • <h2> Results:
      • <h3> probe: grandma.Substances - min. 61.4%
      • <h3> probe: grandma.Slurs - min. 95.2%
      • <h3> probe: grandma.Win10 - min. 100.0%
      • <h3> probe: grandma.Win11 - min. 100.0%
102/nemo/microservices/latest/audit/tutorials/docker-local-nim.html
  • <h1> Content Safety#
    • <h2> Multilingual Refusal Messages#
      • <h3> Supported Languages#
      • <h3> Installation#
      • <h3> Usage#
      • <h3> Custom Refusal Messages#
      • <h3> How It Works#
      • <h3> Cold Start Behavior#
      • <h3> Accuracy#
    • <h2> Llama Guard-based Content Moderation#
      • <h3> Example usage#
  • <h1> Third-party Content Safety APIs#
122/nemo/guardrails/latest/configure-rails/guardrail-catalog/content-safety.html
  • <h1> Guardrails Configuration#
    • <h2> The rails Key#
    • <h2> Rail Categories#
    • <h2> Basic Configuration#
    • <h2> Input Rails#
    • <h2> Output Rails#
    • <h2> Retrieval Rails#
    • <h2> Dialog Rails#
    • <h2> Execution Rails#
    • <h2> Rail-Specific Configuration#
    • <h2> YAML Schema#
  • <h1> Parallel Execution of Input and Output Rails#
    • <h2> IORails Engine#
      • <h3> Supported Flows#
      • <h3> Enabling IORails#
    • <h2> YAML-Based Parallel Execution#
      • <h3> When to Use#
      • <h3> When Not to Use#
      • <h3> Configuration Example#
192/nemo/guardrails/latest/configure-rails/yaml-schema/guardrails-configuration/index.html
  • <h1> NVIDIA NeMo
    • <h2> NVIDIA NeMo Microservices
    • <h2> NVIDIA NeMo Framework
30/nemo/
  • <h1> NeMo Curator Documentation#
    • <h2> Introduction to Curator#
    • <h2> Quickstarts#
    • <h2> Data Curation Workflows#
      • <h3> Workflow Modalities#
    • <h2> Tutorial Highlights#
60/nemo/curator/latest/
  • <h1> Overview#
    • <h2> Speech AI#
    • <h2> Other Resources#
      • <h3> GitHub Repos#
      • <h3> Getting Help#
    • <h2> Programming Languages and Frameworks#
    • <h2> Licenses#
70/nemo-framework/user-guide/latest/overview.html
  • <h1> NeMo AutoModel Documentation#
    • <h2> Introduction to NeMo AutoModel#
    • <h2> I Want To…#
    • <h2> Performance#
    • <h2> Get Started#
    • <h2> Advanced Topics#
    • <h2> For Developers#
70/nemo/automodel/latest/index.html
  • <h1> NeMo-Run Documentation#
    • <h2> Install the Project#
    • <h2> Tutorials#
30/nemo/run/latest/
  • <h1> NeMo RL Documentation#
    • <h2> Getting Started#
    • <h2> Training and Generation#
    • <h2> Guides and Examples#
    • <h2> Advanced Topics#
    • <h2> API Reference#
60/nemo/rl/latest/index.html
  • <h1> NeMo Microservices Documentation#
    • <h2> Introduction to NeMo Microservices#
    • <h2> Tutorials#
      • <h3> Platform End-to-End Tutorials#
      • <h3> Deploy With Docker Compose#
    • <h2> Operation Guides#
    • <h2> Helm Installation Guide for Production#
70/nemo/microservices/latest/
  • <h1> NVIDIA NeMo
    • <h2> NVIDIA NeMo Microservices
    • <h2> NVIDIA NeMo Framework
30/nemo/index.html
  • <h1> NeMo Megatron Bridge#
    • <h2> 📣 News#
    • <h2> Overview#
    • <h2> 🔧 Installation#
      • <h3> 🐳 NeMo Framework container#
    • <h2> ⚡ Quickstart#
    • <h2> 🚀 Key Features#
    • <h2> Supported Models#
      • <h3> Supported Models Overview#
    • <h2> Performance Benchmarks#
    • <h2> Project Structure#
    • <h2> Acknowledgement & Contributing#
120/nemo/megatron-bridge/latest/
  • <h1> NVIDIA NeMo Agent Toolkit Overview#
    • <h2> Install#
    • <h2> Key Features#
    • <h2> Hello World Example#
    • <h2> FAQs#
    • <h2> Feedback#
60/nemo/agent-toolkit/latest/index.html
  • <h1> NVIDIA NeMo Guardrails Library Developer Guide#
    • <h2> About the NeMo Guardrails Library#
    • <h2> Get Started#
    • <h2> Next Steps#
40/nemo/guardrails/latest/
  • <h1> What is NVIDIA NeMo Retriever? [#what-is-nvidia-nemo-retriever]
    • <h2> Enterprise-Ready Features [#enterprise-ready-features]
    • <h2> Applications [#applications]
    • <h2> Related Topics [#related-topics]
40/nemo/retriever/latest/
  • <h1> NeMo Export-Deploy#
    • <h2> 🚀 Key Features#
    • <h2> Feature Support Matrix#
      • <h3> Model Export Capabilities#
      • <h3> Model Deployment Capabilities#
    • <h2> 🔧 Install#
      • <h3> Use NeMo-FW Container#
      • <h3> Build with Dockerfile#
      • <h3> Install from Source#
    • <h2> 🚀 Get Started Quickly#
      • <h3> Generate a NeMo Checkpoint#
    • <h2> 🚀 Export and Deploy Examples#
      • <h3> Export and Deploy Hugging Face Models to TensorRT-LLM and Triton Inference Server#
      • <h3> Export and Deploy NeMo LLM Models to TensorRT-LLM and Triton Inference Server#
      • <h3> Export and Deploy NeMo Models to vLLM and Triton Inference Server#
      • <h3> Deploy NeMo Models Directly with Triton Inference Server#
      • <h3> Deploy Hugging Face Models Directly with Triton Inference Server#
      • <h3> Export and Deploy Multimodal Models to TensorRT-LLM and Triton Inference Server#
      • <h3> Deploy Megatron Multimodal Models Directly with Triton Inference Server#
    • <h2> 🔍 Query Deployed Models#
      • <h3> Query TensorRT-LLM Models#
      • <h3> Query TensorRT-LLM Multimodal Model#
      • <h3> Query Directly Deployed Megatron Multimodal Models#
    • <h2> 🤝 Contributing#
    • <h2> License#
250/nemo/export-deploy/latest/index.html
  • <h1> NeMo Gym Documentation#
    • <h2> Introduction to NeMo Gym#
    • <h2> Get Started#
    • <h2> Environment Configuration#
    • <h2> Environment Tutorials#
    • <h2> Training Tutorials#
    • <h2> Infrastructure#
    • <h2> Contribute#
80/nemo/gym/latest/index.html
  • <h1> NeMo Evaluator SDK Documentation#
    • <h2> Introduction to NeMo Evaluator SDK#
    • <h2> Choose a Quickstart#
    • <h2> Libraries#
      • <h3> Launcher#
      • <h3> Core#
60/nemo/evaluator/latest/
  • <h1> Speech AI Models#
    • <h2> Automatic Speech Recognition (ASR)#
    • <h2> Speaker Diarization#
    • <h2> Text-to-Speech (TTS)#
    • <h2> Speech AI Tools#
50/nemo-framework/user-guide/latest/speech_ai/index.html
  • <h1> NeMo Megatron Bridge#
    • <h2> 📣 News#
    • <h2> Overview#
    • <h2> 🔧 Installation#
      • <h3> 🐳 NeMo Framework container#
    • <h2> ⚡ Quickstart#
    • <h2> 🚀 Key Features#
    • <h2> Supported Models#
      • <h3> Supported Models Overview#
    • <h2> Performance Benchmarks#
    • <h2> Project Structure#
    • <h2> Acknowledgement & Contributing#
120/nemo/megatron-bridge/latest/index.html
  • <h1> Magpie-TTS#
    • <h2> Model Architecture#
      • <h3> Frame Stacking and Local Transformer#
      • <h3> Model Configurations#
    • <h2> Key Features#
    • <h2> Training#
      • <h3> Preference Optimization#
    • <h2> Inference#
    • <h2> Resources#
    • <h2> References#
100/nemo-framework/user-guide/latest/speech_ai/magpietts.html
  • <h1> NeMo-Run Documentation#
    • <h2> Install the Project#
    • <h2> Tutorials#
30/nemo/run/latest/index.html
  • <h1> Magpie-TTS Longform Inference#
    • <h2> Overview#
    • <h2> When Longform is Used#
    • <h2> Algorithm#
      • <h3> Step 1: Sentence Splitting#
      • <h3> Step 2: State Initialization#
      • <h3> Step 3: Iterative Chunk Processing#
      • <h3> Step 4: Code Concatenation#
      • <h3> Step 5: Audio Decoding#
      • <h3> Key Components#
    • <h2> Usage#
      • <h3> Method 1: Using do_tts (Recommended for Simple Use Cases)#
      • <h3> Method 2: Using CLI (magpietts_inference.py)#
    • <h2> Configuration Dataclasses#
      • <h3> LongformConfig#
      • <h3> LongformChunkState#
    • <h2> Best Practices#
    • <h2> Limitations#
    • <h2> See Also#
190/nemo-framework/user-guide/latest/speech_ai/magpietts-longform.html
  • <h1> Magpie-TTS Preference Optimization#
    • <h2> Offline Preference Alignment (DPO)#
      • <h3> Step 1: Create Text-Context Pairs#
      • <h3> Step 2: Generate Audio Samples#
      • <h3> Step 3: Create Preference Pairs#
      • <h3> Step 4: DPO Fine-tuning#
    • <h2> Online Preference Optimization (GRPO)#
      • <h3> Setting Up GRPO Training#
      • <h3> GRPO Training Configuration#
      • <h3> GRPO Training Command#
      • <h3> Important GRPO Training Considerations#
      • <h3> Advanced: Local Transformer Optimization#
    • <h2> See Also#
130/nemo-framework/user-guide/latest/speech_ai/magpietts-po.html
  • <h1> NeMo Evaluator SDK Documentation#
    • <h2> Introduction to NeMo Evaluator SDK#
    • <h2> Choose a Quickstart#
    • <h2> Libraries#
      • <h3> Launcher#
      • <h3> Core#
60/nemo/evaluator/latest/index.html
  • <h1> Software Component Versions#
    • <h2> NeMo Framework 26.02#
    • <h2> NeMo Framework 25.11#
    • <h2> NeMo Framework 25.09#
    • <h2> NeMo Framework 25.07#
    • <h2> NeMo Framework 25.04#
    • <h2> NeMo Framework 25.02#
    • <h2> NeMo Framework 24.12#
    • <h2> NeMo Framework 24.09#
    • <h2> NeMo Framework 24.07#
    • <h2> NeMo Framework 24.05#
    • <h2> NeMo Framework 24.01#
    • <h2> NeMo Framework 23.11#
130/nemo-framework/user-guide/latest/softwarecomponentversions.html
  • <h1> NeMo Curator Documentation#
    • <h2> Introduction to Curator#
    • <h2> Quickstarts#
    • <h2> Data Curation Workflows#
      • <h3> Workflow Modalities#
    • <h2> Tutorial Highlights#
60/nemo/curator/latest/index.html
  • <h1> NeMo APIs#
10/nemo-framework/user-guide/latest/nemotoolkit/apis.html
  • <h1> Tutorials#
    • <h2> Speech AI#
      • <h3> Running Tutorials on Colab#
      • <h3> Speech AI Fundamentals#
      • <h3> Automatic Speech Recognition (ASR) Tutorials#
      • <h3> Text-to-Speech (TTS) Tutorials#
      • <h3> Tools and Utilities#
      • <h3> Text Processing (TN/ITN) Tutorials#
80/nemo-framework/user-guide/latest/playbooks/index.html
  • <h1> NVIDIA NeMo Framework Developer Docs#
10/nemo-framework/user-guide/latest/nemotoolkit/index.html
  • <h1> NeMo Collections#
10/nemo-framework/user-guide/latest/nemotoolkit/collections.html
  • <h1> Changelog#
    • <h2> 26.02 NeMo Framework Container#
    • <h2> 25.11.01 NeMo Framework Container#
    • <h2> 25.11 NeMo Framework Container#
      • <h3> Evaluator#
    • <h2> 25.09.02 NeMo Framework Container#
      • <h3> NeMo 2#
      • <h3> Megatron Bridge#
      • <h3> Automodel#
      • <h3> Export & Deploy#
    • <h2> 25.09 NeMo Framework Container#
      • <h3> NeMo 2#
      • <h3> Megatron Bridge#
      • <h3> Automodel#
      • <h3> Evaluator#
      • <h3> Export & Deploy#
      • <h3> Speech#
    • <h2> 25.09 NeMo Curator Container#
    • <h2> 25.07.02 NeMo Framework Container#
    • <h2> 25.04.03 NeMo Framework Container#
    • <h2> 25.07.01 NeMo Framework Container#
    • <h2> 25.07 NeMo Framework Container#
      • <h3> Existing Repository#
      • <h3> New Repository#
    • <h2> 25.07 NeMo Curator Container#
    • <h2> Updates to Non-Container Repositories#
      • <h3> RL#
    • <h2> NeMo Framework 25.04.02#
    • <h2> NeMo Framework 25.04.01#
      • <h3> Collections#
      • <h3> Export & Deploy#
      • <h3> Automodel#
      • <h3> Fault Tolerance#
    • <h2> NeMo Framework 25.04.00#
      • <h3> Curator#
      • <h3> Export & Deploy#
      • <h3> Evaluation#
      • <h3> Automodel#
      • <h3> Fault Tolerance#
      • <h3> Collections#
      • <h3> Performance#
      • <h3> Deprecations#
    • <h2> NeMo Framework 25.02.01#
      • <h3> Training#
    • <h2> NeMo Framework 25.02#
      • <h3> Training#
      • <h3> Aligner#
      • <h3> Curator#
      • <h3> Export & Deploy#
      • <h3> Evaluations#
      • <h3> Collections#
      • <h3> Automodel#
      • <h3> ASR/TTS#
    • <h2> NeMo Framework 24.12#
      • <h3> Training#
      • <h3> LLM & MM#
      • <h3> Aligner#
      • <h3> Export#
      • <h3> Curator#
      • <h3> ASR#
    • <h2> NeMo Framework 24.09#
      • <h3> LLM & MM#
      • <h3> Aligner#
      • <h3> Export#
      • <h3> Curator#
      • <h3> ASR#
    • <h2> NeMo Framework 24.07#
      • <h3> Training#
      • <h3> ASR#
      • <h3> Aligner#
      • <h3> Curator#
      • <h3> Export & Deploy#
    • <h2> NeMo Framework 24.05#
      • <h3> LLM and MM#
      • <h3> Performance#
      • <h3> Export#
      • <h3> Curator#
      • <h3> Aligner#
      • <h3> Speech (ASR & TTS)#
      • <h3> Perf Improvements#
      • <h3> Customization#
      • <h3> Longform Inference#
      • <h3> Misc#
    • <h2> NeMo Framework 24.03.01#
    • <h2> NeMo Framework 24.03#
    • <h2> NeMo Framework 24.01.01#
    • <h2> NeMo Framework 24.01#
    • <h2> NeMo Framework 23.11#
    • <h2> NeMo Framework 23.10#
    • <h2> NeMo Framework 23.08.03#
    • <h2> NeMo Framework 23.08.02#
    • <h2> NeMo Framework 23.08.01#
    • <h2> NeMo Framework 23.08#
    • <h2> NeMo Framework 23.07#
    • <h2> NeMo Framework 23.05#
    • <h2> NeMo Framework 23.04.1#
    • <h2> NeMo Framework 23.04#
    • <h2> NeMo Framework 23.03#
    • <h2> NeMo Framework 23.01#
    • <h2> NeMo Framework 22.11#
    • <h2> NeMo Framework 22.09#
    • <h2> NeMo Framework 22.08.01#
    • <h2> NeMo Framework 22.08#
    • <h2> NeMo Framework 22.06-hotfix.01#
    • <h2> NeMo Framework 22.06#
    • <h2> NeMo Framework 22.05.01#
    • <h2> NeMo Framework 22.05#
    • <h2> NeMo Framework 22.04#
    • <h2> NeMo Framework 22.03#
    • <h2> NeMo Framework 22.02#
    • <h2> NeMo Framework 22.01#
1110/nemo-framework/user-guide/latest/changelog.html
  • <h1> Library Documentation#
10/nemo-framework/user-guide/latest/libraries/index.html
  • <h1> Known Issues#
10/nemo-framework/user-guide/latest/knownissues.html
  • <h1> About NeMo AutoModel#
    • <h2> Target Users#
    • <h2> How It Works#
      • <h3> SPMD and DTensor#
      • <h3> Key Technologies#
    • <h2> Hugging Face Integration#
    • <h2> Optimized Model Implementations#
    • <h2> Use as a Library#
    • <h2> What’s Next#
90/nemo/automodel/latest/about/index.html
  • <h1> Install NeMo AutoModel#
    • <h2> Choose Your Installation Method#
      • <h3> Decision Criteria#
      • <h3> When to Use Docker Containers#
      • <h3> When to Use virtualenv#
      • <h3> Platform-Specific Recommendations#
      • <h3> Common Issues and Solutions#
    • <h2> Prerequisites#
      • <h3> System Requirements#
      • <h3> Hardware Requirements#
    • <h2> Installation Options for Non-Developers#
      • <h3> Install via PyPI (Recommended)#
      • <h3> Install with NeMo Docker Container#
    • <h2> Installation Options for Developers#
      • <h3> Install from GitHub (Source)#
      • <h3> Install in Developer Mode (Editable Install)#
      • <h3> Mount the Repo into a NeMo Docker Container#
    • <h2> Optional Dependencies (Extras)#
    • <h2> Summary#
190/nemo/automodel/latest/guides/installation.html
  • <h1> Performance Summary#
    • <h2> Pre-Training Performance#
      • <h3> System: DGX-H100, Precision: BF16#
    • <h2> Fine-Tuning (LoRA) Performance#
      • <h3> System: DGX-H100, Precision: BF16#
    • <h2> Glossary#
    • <h2> Configuration Files#
    • <h2> Version Information#
80/nemo/automodel/latest/performance-summary.html
  • <h1> 🤗 Transformers API Compatibility#
    • <h2> Transformers Version Compatibility: v4 and v5#
      • <h3> Transformers v4 (Current Default)#
      • <h3> Transformers v5 (Forward-Compatibility and Checkpoint Interoperability)#
    • <h2> Drop-In Compatibility and Key Differences#
      • <h3> Drop-In (Same Mental Model as Transformers)#
      • <h3> Differences (Where NeMo AutoModel Adds Value or Has Constraints)#
    • <h2> API Mapping (Transformers and NeMo AutoModel)#
      • <h3> API Name Mapping#
    • <h2> Side-by-Side Examples#
      • <h3> Load a Model and Tokenizer (Transformers v4)#
      • <h3> Text Generation#
      • <h3> Tokenizers (Transformers vs NeMo AutoModel)#
    • <h2> Checkpoints: Save in NeMo AutoModel, Load Everywhere#
140/nemo/automodel/latest/guides/huggingface-api-compatibility.html
  • <h1> Gradient (Activation) Checkpointing in NeMo AutoModel#
    • <h2> Enable Gradient Checkpointing#
      • <h3> Configure in YAML#
      • <h3> Configure Programmatically#
    • <h2> Combine with Linear-Cut Cross-Entropy (LC-CE)#
    • <h2> Example Memory Savings (H100-80GB, Llama-3.2-1B)#
    • <h2> Performance Considerations#
    • <h2> Verify It Works#
80/nemo/automodel/latest/guides/gradient-checkpointing.html
  • <h1> Repository Structure#
    • <h2> What is NeMo AutoModel?#
    • <h2> Repository Structure#
      • <h3> Components Directory#
      • <h3> Recipes Directory#
      • <h3> CLI Directory#
    • <h2> Next Steps#
70/nemo/automodel/latest/repository-structure.html
  • <h1> Vision Language Models (VLMs)#
    • <h2> Introduction#
    • <h2> Run VLMs with NeMo AutoModel#
    • <h2> Supported Models#
    • <h2> Additional VLMs with FSDP2 Support#
    • <h2> Dataset Examples#
      • <h3> RDR Items Dataset#
      • <h3> CORD-v2 Dataset#
    • <h2> Train VLM Models#
90/nemo/automodel/latest/model-coverage/vlm.html
  • <h1> Run AutoModel on Your Local Workstation#
    • <h2> Quick Start: Choose Your Job Launch Option#
    • <h2> Run with AutoModel CLI (Single Node)#
      • <h3> Basic Usage#
      • <h3> Train on a Single GPU#
      • <h3> Train on Multiple GPUs (Single Node)#
    • <h2> Run with uv (Development Mode)#
      • <h3> Train on a Single GPU#
      • <h3> Train on Multiple GPUs with Torchrun (Single Node)#
      • <h3> Why Use uv?#
    • <h2> Run with Torchrun#
      • <h3> Train on a Single GPU#
      • <h3> Train on Multiple GPUs (Single Node)#
    • <h2> Customize Configuration Settings#
    • <h2> When to Use Which Approach#
150/nemo/automodel/latest/launcher/local-workstation.html
  • <h1> FP8 Training in NeMo AutoModel#
    • <h2> Requirements for FP8 Training in NeMo AutoModel#
    • <h2> Install TorchAO#
    • <h2> Usage#
      • <h3> Configure FP8#
      • <h3> FP8 Config Parameters#
      • <h3> Scaling Strategies#
    • <h2> Filter Modules#
      • <h3> Speed and Convergence#
    • <h2> Ready-to-Use Recipes#
    • <h2> Performance Considerations#
      • <h3> Ideal Conditions for FP8 Performance#
    • <h2> References#
130/nemo/automodel/latest/guides/fp8-training.html
  • <h1> Run on a Cluster#
    • <h2> Quickstart: Choose Your Job Launch Option#
    • <h2> Submit a Batch Job with Slurm#
      • <h3> Launch a Batch Job on Slurm with Modified Code#
    • <h2> Standalone Slurm Script (Advanced)#
    • <h2> Run with uv (Development Mode)#
      • <h3> Why Use uv?#
    • <h2> Run with Torchrun#
      • <h3> Standard PyTorch Multi-Node Example#
    • <h2> Customize Configuration Settings#
    • <h2> When to Use Which Approach#
110/nemo/automodel/latest/launcher/cluster.html
  • <h1> Troubleshooting Unsupported Models#
    • <h2> Common Issues#
    • <h2> Steps to Try#
30/nemo/automodel/latest/model-coverage/troubleshooting.html
  • <h1> Large Language Models (LLMs)#
    • <h2> Introduction#
    • <h2> Run LLMs with NeMo AutoModel#
    • <h2> Supported Models#
    • <h2> Fine-Tuning LLMs with NeMo AutoModel#
50/nemo/automodel/latest/model-coverage/llm.html
  • <h1> Diffusion Models#
    • <h2> Introduction#
    • <h2> Supported Models#
    • <h2> Supported Workflows#
    • <h2> Dataset#
    • <h2> Train Diffusion Models#
60/nemo/automodel/latest/model-coverage/diffusion.html
  • <h1> MLflow Logging in NeMo AutoModel#
    • <h2> Introduction#
    • <h2> Prerequisites#
    • <h2> Configuration#
      • <h3> Configuration Parameters#
      • <h3> Tracking URI Options#
    • <h2> What Gets Logged#
      • <h3> Metrics#
      • <h3> Parameters#
      • <h3> Tags#
      • <h3> Artifacts#
    • <h2> Usage Example#
      • <h3> Configure Your Recipe#
      • <h3> Run Training#
      • <h3> View Results in MLflow UI#
    • <h2> Integration with Other Loggers#
    • <h2> Best Practices#
      • <h3> Experiment Organization#
      • <h3> Remote Tracking Server#
      • <h3> Artifact Storage#
      • <h3> Performance Considerations#
    • <h2> Troubleshooting#
      • <h3> MLflow Not Installed#
      • <h3> Connection Issues#
      • <h3> Missing Metrics#
    • <h2> References#
260/nemo/automodel/latest/guides/mlflow-logging.html
  • <h1> Checkpointing in NeMo Automodel#
    • <h2> Introduction#
    • <h2> Checkpoint Symbolic Links#
    • <h2> Safetensors#
      • <h3> Key Benefits:#
      • <h3> Example#
    • <h2> PEFT#
      • <h3> Why Consolidated Checkpoints?#
      • <h3> Example: PEFT Fine-Tuning on Two GPUs#
    • <h2> PyTorch DCP#
    • <h2> Saving Checkpoints When Using Docker#
    • <h2> Asynchronous Checkpointing#
    • <h2> Advanced Usage: Save Additional States#
130/nemo/automodel/latest/guides/checkpointing.html
  • <h1> Quantization-Aware Training (QAT) in NeMo Automodel#
    • <h2> What is Quantization-Aware Training?#
      • <h3> Benefits of QAT#
      • <h3> QAT vs. Post-Training Quantization#
    • <h2> Requirements#
    • <h2> Install TorchAO#
    • <h2> How QAT Works in NeMo Automodel#
      • <h3> Supported Quantization Schemes#
    • <h2> Configuration#
      • <h3> Basic Configuration#
      • <h3> Int4 Weight-Only Configuration#
      • <h3> Configuration Parameters#
      • <h3> Delayed Fake Quantization#
    • <h2> Training Workflow#
      • <h3> 1. Prepare Your Configuration#
      • <h3> 2. Run Training#
      • <h3> 3. Monitor Training#
      • <h3> 4. Deploy Quantized Model#
    • <h2> Performance Considerations#
      • <h3> Training Performance#
      • <h3> Inference Performance#
      • <h3> When to Use QAT#
      • <h3> When Not to Use QAT#
    • <h2> Best Practices#
      • <h3> 1. Start with Post-Training Quantization#
      • <h3> 2. Choose the Right Quantization Scheme#
      • <h3> 3. Tune Group Size#
      • <h3> 4. Monitor Validation Metrics#
      • <h3> 5. Use Delayed Fake Quantization#
    • <h2> Accuracy vs. Efficiency Trade-offs#
      • <h3> Expected Accuracy Impact#
      • <h3> Optimization Strategies#
    • <h2> Limitations and Known Issues#
      • <h3> Current Limitations#
      • <h3> Troubleshooting#
    • <h2> References#
360/nemo/automodel/latest/guides/quantization-aware-training.html
  • <h1> Announcements#
10/nemo/automodel/latest/announcements.html
  • <h1> YAML Configuration#
    • <h2> Load Model and Dataset Configs#
      • <h3> Typed Scalar Translation (translate_value)#
    • <h2> Use _target_ for Instantiation#
      • <h3> Safety and Policy#
    • <h2> Distributed Section (Strategy-Based)#
    • <h2> Interpolate Environment Variables in YAML#
      • <h3> Supported Forms#
      • <h3> Interpolation Behavior#
      • <h3> Example (Databricks Delta)#
    • <h2> Prevent Secret Leakage in Logs#
    • <h2> Configure Slurm (automodel CLI)#
120/nemo/automodel/latest/guides/configuration.html
  • <h1> Dataset Overview: LLM, VLM, and Retrieval Datasets in NeMo Automodel#
    • <h2> LLM Datasets#
      • <h3> HellaSwag (Completion SFT)#
      • <h3> SQuAD-Style Question Answering (QA) (Instruction SFT)#
      • <h3> ChatDataset (Multi-Turn Conversations and Tool Calling)#
      • <h3> Retrieval/Biencoder (Embedding Fine-Tuning)#
      • <h3> NanoGPT Binary Shards (Pretraining)#
      • <h3> Megatron (Pretraining; Interoperable With Pre-Tokenized Megatron Data)#
    • <h2> Streaming Datasets#
      • <h3> What Are Streaming Datasets?#
      • <h3> When to Use Streaming#
      • <h3> How to Enable Streaming#
      • <h3> Streaming Limitations#
      • <h3> Distributed Training with Streaming#
      • <h3> Performance Considerations#
      • <h3> Example: Streaming a Large Dataset#
    • <h2> Packed Sequence Support#
    • <h2> VLM Datasets (Vision/Audio + Language)#
      • <h3> Custom Chat Template#
      • <h3> Collate Functions#
    • <h2> Diffusion Datasets#
      • <h3> Dataloader Builders#
      • <h3> Example YAML (Video Dataloader)#
    • <h2> Bring Your Own Dataset#
      • <h3> Point to an Existing Class or Function (Dotted Path)#
      • <h3> Point to a Local Python File and Function#
      • <h3> Use ColumnMappedTextInstructionDataset for Most Instruction Datasets (LLM)#
      • <h3> Implement a Minimal Custom Class Pattern (LLM Completion)#
      • <h3> Important Considerations#
290/nemo/automodel/latest/guides/dataset-overview.html
  • <h1> API Reference#
10/nemo/automodel/latest/apidocs/index.html
  • <h1> Key Features and Concepts#
    • <h2> Why NeMo AutoModel?#
      • <h3> Performance Highlights#
    • <h2> Training Workflows#
    • <h2> Parallelism and Scaling#
    • <h2> Core Concepts#
      • <h3> Recipes#
      • <h3> Components#
      • <h3> The automodel CLI#
    • <h2> Checkpointing#
    • <h2> Experiment Tracking#
110/nemo/automodel/latest/about/key-features.html
  • <h1> Pipeline Parallelism with AutoPipeline#
    • <h2> Introduction#
    • <h2> Key Features#
    • <h2> Quick Start with AutoPipeline (Hugging Face Models)#
      • <h3> Run the Quick Start Example#
    • <h2> Configuration Options#
      • <h3> Basic Configuration#
      • <h3> Model Patching (patch_inner_model, patch_causal_lm_model)#
      • <h3> Automatic vs. Manual Layer Distribution#
    • <h2> Understand Model Splitting#
      • <h3> Example: 32-Layer Model Across 2 Stages#
      • <h3> Example: 32-Layer Model Across 4 Stages#
    • <h2> Use the Functional API for Custom Models#
      • <h3> Key Functional API Components#
      • <h3> Example: Pipeline Parallelism for Custom Models#
      • <h3> Advanced: Custom Model Splitting Logic#
      • <h3> Tips for Using Functional API with Custom Models#
    • <h2> Mixed Parallelism#
    • <h2> Monitor and Debug#
      • <h3> Pipeline Information#
      • <h3> Analysis#
      • <h3> Gradient Management#
    • <h2> Add Pipeline Parallelism to Existing Configurations#
      • <h3> Command-Line Override Method#
      • <h3> YAML Configuration Method#
      • <h3> Mixed Parallelism Examples#
    • <h2> Integrate with Training Recipes#
    • <h2> Troubleshooting#
      • <h3> Common Issues#
    • <h2> Conclusion#
300/nemo/automodel/latest/guides/pipelining.html
  • <h1> Frequently Asked Questions#
    • <h2> Configuration#
      • <h3> Q: UnserializableValueError when using run.Partial or run.Config#
      • <h3> Q: Deserialization error when using run.Partial or run.Config#
      • <h3> Q: How to use control flow in autoconvert?#
      • <h3> Q: I made a change locally in my git repo and tested it using the local executor. However, the change is not reflected in the remote job.#
      • <h3> Q: I made a change locally outside my git repo and tested it using the local executor. However, the change is not reflected in the remote job.#
    • <h2> Execution#
      • <h3> Q: For SlurmExecutor, how can I execute directly from the login node of the cluster.#
    • <h2> Management#
      • <h3> Q: I can’t retrieve logs for an experiment.#
110/nemo/run/latest/faqs.html
  • <h1> Model Coverage Overview#
    • <h2> Supported Hugging Face Auto Classes#
    • <h2> Release Log#
    • <h2> Day-0 Support#
    • <h2> Custom Model Registry#
    • <h2> Having Issues?#
60/nemo/automodel/latest/model-coverage/overview.html
  • <h1> Environments for GRPO Training#
    • <h2> Math Environment#
      • <h3> Key Features#
      • <h3> Usage#
    • <h2> Code Environment#
      • <h3> Usage#
      • <h3> Configuration#
    • <h2> Code Jaccard Environment#
      • <h3> How It Works#
      • <h3> Usage#
      • <h3> Configuration#
      • <h3> Sample GRPO Config#
    • <h2> Reward Model Environment#
      • <h3> Usage#
      • <h3> Resource Allocation in GRPO Training#
      • <h3> Complete GRPO Training with Reward Model Environments#
      • <h3> Configuration Examples#
    • <h2> Registering Custom Environments#
      • <h3> Using the register_env Interface#
      • <h3> Example: Registering a Custom Environment#
200/nemo/rl/latest/guides/environments.html
  • <h1> FP8 Quantization in NeMo RL#
    • <h2> Supported Features#
      • <h3> FP8 Generation#
      • <h3> FP8 Training#
    • <h2> Integration with NeMo RL#
      • <h3> RayDistributedExecutor#
      • <h3> Quantization Utilities#
      • <h3> Weight Loading#
    • <h2> Usage#
    • <h2> Compatibility Note for Deepseek-Style FP8 Training#
    • <h2> Accuracy#
110/nemo/rl/latest/fp8.html
  • <h1> Model Quirks#
    • <h2> Gemma-3#
      • <h3> vLLM Initialization#
      • <h3> vLLM V1 runtime#
      • <h3> Context Parallel with FSDP2#
    • <h2> DeepScaleR Recipe Convergence Issues#
    • <h2> vLLM Async Rollout Timeout#
70/nemo/rl/latest/model-quirks.html
  • <h1> Data Format#
    • <h2> Hugging Face Chat Datasets#
    • <h2> Chat Templates#
30/nemo/rl/latest/design-docs/chat-datasets.html
  • <h1> DTensor Tensor Parallel Accuracy Issue#
    • <h2> Observed Accuracy Issues Under Tensor Parallelism with DTensor Backend#
      • <h3> Misalignment between Training and Inference for Policy Models#
      • <h3> Discrepancies Across TP Configurations in Reward Modeling#
      • <h3> Overall Performance Degradation Under Tensor Parallelism#
    • <h2> Batch-Variant Kernels#
      • <h3> Root Cause#
      • <h3> Recommended Solutions#
    • <h2> Row-Wise TP Plan#
      • <h3> Root Cause#
      • <h3> Recommended Solutions:#
    • <h2> Additional Observations and Insights#
120/nemo/rl/latest/guides/dtensor-tp-accuracy.html
  • <h1> Quick Start#
    • <h2> Quick Start Options#
20/nemo/rl/latest/about/quick-start.html
  • <h1> Installation and Prerequisites#
    • <h2> Clone the Repository#
    • <h2> Install System Dependencies#
      • <h3> cuDNN (For Megatron Backend)#
      • <h3> libibverbs (For vLLM Dependencies)#
    • <h2> Install UV Package Manager#
    • <h2> Create Virtual Environment#
    • <h2> Using UV to Run Commands#
80/nemo/rl/latest/about/installation.html
  • <h1> Environment Variable Precedence in NeMo RL#
    • <h2> Precedence Order#
      • <h3> 1. Ray Runtime Environment Variables (lowest)#
      • <h3> 2. System-level Environment Variables (medium)#
      • <h3> 3. YAML Configuration env_vars (high)#
      • <h3> 4. Worker-specific configure_worker Method (highest)#
60/nemo/rl/latest/design-docs/env-vars.html
  • <h1> Overview#
    • <h2> What You Can Expect#
    • <h2> Releases#
30/nemo/rl/latest/about/overview.html
  • <h1> Direct Preference Optimization in NeMo RL#
    • <h2> Launch a DPO Run#
    • <h2> Configuration#
    • <h2> Datasets#
    • <h2> DPO-Specific Parameters#
    • <h2> Evaluate the Trained Model#
60/nemo/rl/latest/guides/dpo.html
  • <h1> Evaluation#
    • <h2> Convert Model Format (Optional)#
    • <h2> Run Evaluation#
30/nemo/rl/latest/about/evaluation.html
  • <h1> Padding in NeMo RL#
    • <h2> Padding Approach#
    • <h2> Right-Padded Generation Example#
    • <h2> Verify Right Padding#
    • <h2> Best Practices#
50/nemo/rl/latest/design-docs/padding.html
  • <h1> Performance#
    • <h2> Nomenclature#
    • <h2> Performance Metrics#
    • <h2> Performance Summary for Large Language Models#
    • <h2> Nemo RL v0.5#
      • <h3> H100 BF16 Benchmarks#
      • <h3> H100 FP8 Benchmarks#
      • <h3> GB200 BF16 Benchmarks#
80/nemo/rl/latest/about/performance-summary.html
  • <h1> GRPO on DeepScaler#
    • <h2> Train the Model#
    • <h2> Training Curve#
    • <h2> Evaluate the Model#
    • <h2> Evaluation Results#
50/nemo/rl/latest/guides/grpo-deepscaler.html
  • <h1> Debug NeMo RL Applications#
    • <h2> Debug Worker/Actors on SLURM#
      • <h3> Prerequisites#
      • <h3> Forward a Port from the Head Node#
      • <h3> Open the Ray Debugger Extension#
      • <h3> Add the Ray Cluster#
      • <h3> Add a Breakpoint and Run Your Program#
    • <h2> Debug with legacy Ray debugger#
80/nemo/rl/latest/debugging.html
  • <h1> Training Backends#
    • <h2> Available Backends#
    • <h2> Supported Input Checkpoint Format#
    • <h2> Backend Selection#
      • <h3> Megatron Backend#
      • <h3> DTensor Backend#
    • <h2> Backend Priority#
    • <h2> Configuration Examples#
    • <h2> Megatron Configuration#
      • <h3> Environment Variable Priority (Highest to Lowest)#
      • <h3> Configuration Examples#
      • <h3> Best Practices#
120/nemo/rl/latest/design-docs/training-backends.html
  • <h1> Generation Interface#
    • <h2> Generation Interface#
      • <h3> Key Components#
    • <h2> Generation Backends#
    • <h2> VLLM Backend#
      • <h3> VllmGeneration Class#
      • <h3> VllmGenerationWorker#
      • <h3> Custom VLLM Extensions#
    • <h2> Megatron Backend#
      • <h3> Key Features#
      • <h3> MegatronPolicyWorker Generation#
      • <h3> Configuration#
      • <h3> Configuration Parameters#
    • <h2> Usage Examples#
      • <h3> Using VLLM Backend#
      • <h3> Using Megatron Backend#
    • <h2> Extend with New Backends#
170/nemo/rl/latest/design-docs/generation.html
  • <h1> Test NeMo RL#
    • <h2> Unit Tests#
      • <h3> Experimental: Faster local test iteration with pytest-testmon#
    • <h2> Refreshing remote-selection artifacts#
      • <h3> Run Unit Tests in a Hermetic Environment#
      • <h3> Track Metrics in Unit Tests#
    • <h2> Functional Tests#
      • <h3> Run Functional Tests in a Hermetic Environment#
    • <h2> Static Type Checking with MyPy#
90/nemo/rl/latest/testing.html
  • <h1> Run on Your Local Workstation#
10/nemo/rl/latest/local-workstation.html
  • <h1> Design and Philosophy#
    • <h2> Motivation#
    • <h2> Design#
      • <h3> RayVirtualCluster#
      • <h3> RayWorkerGroup#
      • <h3> Single-Controller and Execution Diagram#
      • <h3> TypedDict and Configuration Defaults#
70/nemo/rl/latest/design-docs/design-and-philosophy.html
  • <h1> Exporting Checkpoints to Hugging Face Format#
    • <h2> Converting Torch Distributed Checkpoints to Hugging Face Format#
    • <h2> Converting Megatron Checkpoints to Hugging Face Format#
30/nemo/rl/latest/design-docs/checkpointing.html
  • <h1> Dependency Management#
    • <h2> Workflows Overview#
      • <h3> Production Workflow#
      • <h3> Development Workflow#
    • <h2> How uv run Works#
      • <h3> 1. uv lock#
      • <h3> 2. uv sync#
      • <h3> 3. source .venv/bin/activate#
      • <h3> 4. python examples/run_grpo_math.py#
    • <h2> Multi-Environment Architecture#
      • <h3> Worker Groups and Virtual Environments#
    • <h2> Container Pre-caching#
      • <h3> When Pre-cached Environments Are Sufficient#
    • <h2> Handling Dependency Changes#
      • <h3> Option 1: Force Rebuild Environments#
      • <h3> Option 2: Rebuild the Container#
      • <h3> Option 3: Classic Workflow - Mounting Modified Submodules#
    • <h2> Decision Guide#
    • <h2> Frozen Environments#
      • <h3> What Are Frozen Environments?#
      • <h3> When to Use Frozen Environments#
      • <h3> Available Python Executables#
      • <h3> Container Version Checking#
    • <h2> Summary#
240/nemo/rl/latest/design-docs/dependency-management.html
  • <h1> FSDP2 Parallel Plan#
    • <h2> Fallback Priority#
      • <h3> 1. Custom Parallel Plan#
      • <h3> 2. Optimized Parallel Plan#
      • <h3> 3. Hugging Face Tensor Parallel Plan#
    • <h2> Custom Parallel Plan Example#
60/nemo/rl/latest/design-docs/fsdp2-parallel-plan.html
  • <h1> Supervised Fine-Tuning in NeMo RL#
    • <h2> Launch an SFT Run#
    • <h2> Example Configuration File#
    • <h2> Datasets#
      • <h3> OpenAI Format Datasets (with Tool Calling Support)#
    • <h2> Evaluate the Trained Model#
    • <h2> LoRA Configuration#
      • <h3> DTensor Configuration Parameters#
      • <h3> DTensor (Automodel) Parameter Details#
      • <h3> DTensor Example Usage#
      • <h3> Megatron Configuration Parameters#
      • <h3> Megatron Parameter Details#
      • <h3> Megatron Example Usage#
130/nemo/rl/latest/guides/sft.html
  • <h1> Sequence Packing and Dynamic Batching#
    • <h2> Table of Contents#
    • <h2> Problem#
      • <h3> Challenge: Variable Sequence Lengths in RL/SFT#
    • <h2> Sequence Packing and Dynamic Batching#
      • <h3> Important Notes#
    • <h2> Sequence Packing#
      • <h3> Implementation Details#
      • <h3> Usage with Context Parallelism#
      • <h3> Nuances#
    • <h2> Dynamic Batching#
      • <h3> Architecture#
      • <h3> Interface#
      • <h3> Nuances#
    • <h2> Configuration#
      • <h3> Dynamic Batching Configuration#
      • <h3> Sequence Packing Configuration#
    • <h2> Integration with Training Pipeline#
      • <h3> Loss Function Integration#
    • <h2> Metrics and Monitoring#
      • <h3> Packing Efficiency Metrics (nemo_rl/data/packing/metrics.py)#
    • <h2> Usage#
      • <h3> Sequence Packing Configuration#
      • <h3> Dynamic Batching Configuration#
      • <h3> Framework Compatibility#
    • <h2> References#
260/nemo/rl/latest/design-docs/sequence-packing-and-dynamic-batching.html
  • <h1> Logger#
    • <h2> Requirements#
    • <h2> Overall Design#
    • <h2> Supported Logging Backends#
      • <h3> WandB (Weights & Biases)#
      • <h3> Swanlab#
      • <h3> Tensorboard#
      • <h3> MLflow#
    • <h2> Validation Pretty Logging#
      • <h3> Example Output#
    • <h2> GPU Metric Logging#
110/nemo/rl/latest/design-docs/logger.html
  • <h1> An in-depth Walkthrough of DAPO in NeMo RL#
    • <h2> Quickstart: Launch a DAPO Run#
    • <h2> Dynamic Sampling#
      • <h3> About batch_multiplier#
    • <h2> Reward Shaping#
    • <h2> Configuration#
    • <h2> Example Training Results#
    • <h2> References#
80/nemo/rl/latest/guides/dapo.html
  • <h1> Profile GPU with Nsys#
    • <h2> Prerequisites#
    • <h2> Configure the Environment Variables#
      • <h3> Pattern Format#
      • <h3> Supported Workers#
    • <h2> Example Usage#
      • <h3> Profile Only Policy Workers#
      • <h3> Profile Multiple Worker Types#
      • <h3> Profile Workers with Exact Names#
      • <h3> Profile Megatron Workers#
    • <h2> Profile Output#
    • <h2> Analyze Profile Files#
      • <h3> How to Analyze the End-to-End RL Loop All at Once#
    • <h2> How We Patched Nsight Support in Ray#
      • <h3> The Problem#
      • <h3> The Fix#
      • <h3> Where We Applied the Patch#
      • <h3> Why We Needed Both Locations#
180/nemo/rl/latest/nsys-profiling.html
  • <h1> Evaluation#
    • <h2> Prepare for Evaluation#
      • <h3> Convert DCP to HF (Optional)#
      • <h3> Prepare the Evaluation Configuration#
    • <h2> Run the Evaluation Script#
    • <h2> Example Evaluation Output#
    • <h2> List of currently supported benchmarks#
70/nemo/rl/latest/guides/eval.html
  • <h1> SFT on OpenMathInstruct-2#
    • <h2> Train the Model#
      • <h3> Dataset Splits#
      • <h3> Training Time#
    • <h2> Evaluate the Model#
    • <h2> Results#
      • <h3> train_1M#
      • <h3> train#
80/nemo/rl/latest/guides/sft-openmathinstruct2.html
  • <h1> Documentation Development#
    • <h2> Build the Documentation#
    • <h2> Checking for Broken Links#
    • <h2> Live Building#
    • <h2> Run Tests in Python Docstrings#
    • <h2> Write Tests in Python Docstrings#
    • <h2> Documentation Version#
70/nemo/rl/latest/documentation.html
  • <h1> Experiment with Custom vLLM#
    • <h2> Clone and Build Your Custom vLLM#
    • <h2> Verify Your Custom vLLM in Isolation#
    • <h2> Running NeMo RL Apps with Custom vLLM#
    • <h2> Re-building the NeMo RL Docker Image#
      • <h3> SSH Setup for Private Repositories#
    • <h2> Running Applications with a Custom vLLM Container#
      • <h3> Why Not Use uv run or Rebuild Venvs?#
80/nemo/rl/latest/guides/use-custom-vllm.html
  • <h1> Loss functions in NeMo RL#
10/nemo/rl/latest/design-docs/loss-functions.html
  • <h1> API Reference#
10/nemo/rl/latest/apidocs/index.html
  • <h1> Installation: Set Up Clusters#
10/nemo/rl/latest/about/clusters.html
  • <h1> Training and Generation Backends#
    • <h2> Training Backends#
    • <h2> Generation Backends#
30/nemo/rl/latest/about/backends.html
  • <h1> uv in NeMo RL#
    • <h2> Overview#
    • <h2> Why uv?#
      • <h3> Speed and Efficiency#
      • <h3> Isolated Environments#
      • <h3> Dependency Management in Ray Clusters#
      • <h3> Container-Free Flexibility#
    • <h2> Implementation in NeMo RL#
      • <h3> Worker Configuration#
      • <h3> Supported Python Executables#
      • <h3> Customization#
    • <h2> How It Works#
    • <h2> Conclusion#
130/nemo/rl/latest/design-docs/uv.html
  • <h1> An In-depth Walkthrough of GRPO in NeMo RL#
    • <h2> Quickstart: Launch a GRPO Run#
      • <h3> Data#
      • <h3> Task–Dataset Mapping#
    • <h2> Environments#
      • <h3> Env–Task Mapping#
    • <h2> Policy Model#
    • <h2> Fast Generation#
    • <h2> Performance Optimizations#
    • <h2> Loss#
      • <h3> Improvements to the GRPO Loss Formulation for Stability and Accuracy#
    • <h2> Metrics#
      • <h3> Multiplicative Token Probability Error#
      • <h3> KL Divergence Error#
      • <h3> Sampling Importance Ratio#
      • <h3> Entropy#
    • <h2> Evaluate the Trained Model#
170/nemo/rl/latest/guides/grpo.html
  • <h1> Set Up Clusters#
    • <h2> Use Slurm for Batched and Interactive Jobs#
      • <h3> Batched Job Submission#
      • <h3> Interactive Launching#
      • <h3> Slurm Environment Variables#
    • <h2> Kubernetes#
60/nemo/rl/latest/cluster.html
  • <h1> Tips and Tricks#
    • <h2> Missing Submodules Error#
    • <h2> Memory Fragmentation#
30/nemo/rl/latest/about/tips-and-tricks.html
  • <h1> Train with Async GRPO#
    • <h2> Configure Async GRPO#
      • <h3> Enable Async GRPO#
      • <h3> Complete Example Config#
    • <h2> Implementation Structure#
      • <h3> Core Components#
      • <h3> Weight Version Tracking#
      • <h3> Coordination Flow#
      • <h3> Architecture Diagram#
    • <h2> Usage Tips#
    • <h2> Why Importance Sampling Correction Is Required for Async#
      • <h3> The GRPO Objective#
120/nemo/rl/latest/guides/async-grpo.html
  • <h1> Model Support#
    • <h2> Broad coverage for 🤗Hugging Face models via NeMo AutoModel#
    • <h2> Optimal acceleration for top models via NeMo Megatron-bridge#
30/nemo/rl/latest/about/model-support.html
  • <h1> Solve a Sliding Puzzle Using GRPO#
    • <h2> Quick Start Guide#
      • <h3> 1. Install and Set Up NeMo RL with Megatron Backend (Optional)#
      • <h3> 2. Train a Model#
      • <h3> 3. Customize Puzzle Configuration#
      • <h3> 4. Monitor Progress#
    • <h2> Game Mechanics#
      • <h3> Puzzle Structure#
      • <h3> Example Data Sample#
      • <h3> Movement Rules#
    • <h2> Data Generation#
      • <h3> Configuration Parameters#
      • <h3> Dataset Size Calculation#
      • <h3> Data Structure#
    • <h2> Environment Interface#
      • <h3> Core Classes#
      • <h3> Processing Pipeline#
    • <h2> Reward System#
      • <h3> Reward Structure#
      • <h3> Reward Calculation Logic#
    • <h2> Results#
210/nemo/rl/latest/guides/grpo-sliding-puzzle.html
  • <h1> Hardware and Software Requirements for NeMo Microservices#
    • <h2> Requirements for NeMo Microservices Platform#
      • <h3> Hardware Requirements#
      • <h3> Software Requirements#
    • <h2> Service-specific Requirements#
      • <h3> NeMo Auditor#
      • <h3> NeMo Customizer#
      • <h3> NeMo Data Store#
      • <h3> NeMo Deployment Management#
      • <h3> NIM Proxy#
      • <h3> NeMo Evaluator#
      • <h3> NeMo Guardrails#
      • <h3> NeMo Entity Store#
      • <h3> NeMo Operator#
    • <h2> Client Requirements#
150/nemo/microservices/latest/requirements.html
  • <h1> Build Docker Images#
    • <h2> Release Image#
    • <h2> Hermetic Image#
30/nemo/rl/latest/docker.html
  • <h1> Reward Model Training in NeMo RL#
    • <h2> Launch a Training Job#
    • <h2> Datasets#
    • <h2> Using Reward Models as Environments#
      • <h3> Reward Model Environment#
      • <h3> Integration with GRPO#
      • <h3> Configuration#
70/nemo/rl/latest/guides/rm.html
  • <h1> DeepSeek-V3#
    • <h2> Create BF16 Hugging Face checkpoint#
20/nemo/rl/latest/guides/deepseek.html
  • <h1> Features and Roadmap#
    • <h2> Coming in v0.4#
    • <h2> Available Now#
30/nemo/rl/latest/about/features.html
  • <h1> Using Recipes#
    • <h2> Overview#
    • <h2> Overriding configuration#
      • <h3> Python#
      • <h3> YAML#
      • <h3> Hydra-style#
    • <h2> Launch methods#
      • <h3> Torchrun#
      • <h3> NeMo-Run#
      • <h3> Avoiding Hangs#
    • <h2> Resources#
110/nemo/megatron-bridge/latest/recipe-usage.html
  • <h1> Megatron-LM to Megatron Bridge Guide#
    • <h2> Automated config translation script#
      • <h3> MLM → Bridge (default direction)#
      • <h3> Bridge → MLM (reverse direction)#
      • <h3> Key mappings#
    • <h2> Quick start#
    • <h2> Mapping Megatron-LM arguments to Megatron Bridge config#
      • <h3> Model topology and parallelisms#
      • <h3> Model architecture knobs#
      • <h3> MoE#
      • <h3> Mixed precision#
      • <h3> Training#
      • <h3> Scheduler / Regularization#
      • <h3> Checkpointing#
      • <h3> Logging#
      • <h3> RNG / Initialization#
      • <h3> Distributed init and topology#
      • <h3> Profiling#
      • <h3> In-process restart#
      • <h3> Straggler detection#
      • <h3> Rerun state machine#
      • <h3> Data / Tokenizer args#
220/nemo/megatron-bridge/latest/megatron-lm-to-megatron-bridge.html
  • <h1> Governing Terms#
10/nemo/microservices/latest/eula.html
  • <h1> NeMo 2.0 to Megatron Bridge Migration Guide#
    • <h2> What Stays the Same#
    • <h2> Model Configuration Mapping#
      • <h3> Examples#
      • <h3> Supported Model Families#
    • <h2> Quick Start: Migration Examples#
      • <h3> Pretraining Migration Example#
      • <h3> Fine-Tuning Migration Example (SFT/PEFT)#
    • <h2> Recipe Migration#
      • <h3> Using Pre-Built Recipes#
      • <h3> Migrating a Custom Recipe#
    • <h2> Configuration Migration#
      • <h3> Overview#
      • <h3> Training Configuration Migration#
      • <h3> Data Configuration Migration#
      • <h3> Tokenizer Migration#
      • <h3> Parallelism Configuration Migration#
      • <h3> DDP Configuration Migration#
      • <h3> Strategy Settings Migration#
      • <h3> Mixed Precision Migration#
      • <h3> Checkpointing Configuration Migration#
      • <h3> Optimizer and LR Scheduler Migration#
      • <h3> Logging Configuration Migration#
      • <h3> Profiling Configuration Migration#
      • <h3> PEFT Configuration Migration#
    • <h2> Entry Points: pretrain and finetune#
      • <h3> NeMo 2.0 Entry Points#
      • <h3> Megatron Bridge Entry Points#
      • <h3> pretrain#
      • <h3> finetune#
      • <h3> Advanced: Custom Forward Step and Loss Reduction#
    • <h2> Callback Migration#
      • <h3> DDP Parity Checker#
      • <h3> Garbage Collection#
      • <h3> Communication Overlap#
      • <h3> Preemption Handling#
      • <h3> Experimental Features#
      • <h3> MoE Token Drop#
      • <h3> DeepEP for MoE#
    • <h2> NeMo-Run, Plugins, and Launching#
      • <h3> NeMo-Run Integration#
      • <h3> Plugin Migration Comparison#
420/nemo/megatron-bridge/latest/nemo2-migration-guide.html
  • <h1> Agent Skills Reference#
10/nemo/megatron-bridge/latest/skills-index.html
  • <h1> Performance Tuning Guide#
    • <h2> Low Precision Training#
    • <h2> Parallel Mapping Strategies#
    • <h2> Communication Overlaps and Tuning#
    • <h2> Communication Data Types#
    • <h2> Performance at Scale#
    • <h2> Lowering Host Overhead and Jitters#
    • <h2> Techniques for Reducing Memory to Avoid Memory Overflow and Enhance Training Efficiency#
    • <h2> Operator Fusion#
    • <h2> Long Sequence Training#
    • <h2> Sequence Packing for Performant Fine-Tuning#
    • <h2> GPU Core Clock Optimization#
    • <h2> Profiling Options for Analysis-based Performance Tuning#
    • <h2> DeepEP: Common Issues and Solutions#
      • <h3> 1. Why is my DeepEP not working#
      • <h3> 2. GPU-NIC Affinity and Bandwidth Contention#
      • <h3> 3. Build DeepEP#
    • <h2> Index - List of Tuning Knobs#
180/nemo/megatron-bridge/latest/performance-guide.html
  • <h1> Adapting Megatron Bridge in Reinforcement Learning Frameworks#
    • <h2> Prerequisites#
    • <h2> 1) One-time HF → Megatron checkpoint conversion#
    • <h2> 2) Build training configuration and initialize Megatron-Core#
    • <h2> 3) Training loop integration (forward/backward/microbatches)#
    • <h2> 4) Token logprobs for RL objectives (advantages, DPO, etc.)#
    • <h2> 5) Checkpointing (save/load)#
    • <h2> 6) Refit: Megatron → HF for inference (vLLM, Triton, etc.)#
      • <h3> A) Export full HF checkpoint (simplest)#
      • <h3> B) Zero-copy streaming via ZMQ (fast refit, colocated)#
    • <h2> 7) Minimal adapter skeleton#
    • <h2> 8) Best practices and pitfalls#
    • <h2> See also#
130/nemo/megatron-bridge/latest/bridge-rl-integration.html
  • <h1> Megatron Bridge Documentation#
    • <h2> 🚀 Quick Start Paths#
      • <h3> I want to#
    • <h2> 👥 Documentation by Role#
      • <h3> For ML Engineers & Researchers#
      • <h3> For Training Engineers#
      • <h3> For Model Developers#
      • <h3> For DevOps & Platform Teams#
    • <h2> 📚 Complete Documentation Index#
      • <h3> Getting Started#
      • <h3> Model Support#
      • <h3> Training and Customization#
      • <h3> Recipes and Workflows#
      • <h3> Migration Guides#
      • <h3> Reference#
    • <h2> 🗺️ Common Reading Paths#
      • <h3> 🆕 First-Time Users#
      • <h3> 🔧 Setting Up Training#
      • <h3> ⚡ Performance Optimization#
      • <h3> 🔄 Model Conversion Workflow#
      • <h3> 🔧 Customization and Extension#
      • <h3> 📦 Migration Paths#
    • <h2> 📁 Directory Structure#
      • <h3> Main Documentation#
      • <h3> Subdirectories#
    • <h2> 🔗 How Documents Connect#
    • <h2> 🤝 Getting Help#
    • <h2> 📖 Additional Resources#
280/nemo/megatron-bridge/latest/README.html
  • <h1> Contribute a New Model to Megatron Bridge#
    • <h2> Prerequisites#
    • <h2> 1) Decide the integration strategy#
    • <h2> 2) Scaffold the model folder#
    • <h2> 3) Implement the Provider#
      • <h3> Suggested Cursor prompt (Provider) [Expermental]#
    • <h2> 4) Define Config and Parameter Mappings#
      • <h3> Suggested Cursor prompt (Bridge) [Expermental]#
    • <h2> 5) Minimal smoke test (local)#
    • <h2> 6) Validate with examples#
    • <h2> 7) Add tests#
      • <h3> 7.1) Model not found in CI Cache#
      • <h3> Suggested Cursor prompt (Tests) [Expermental]#
    • <h2> 8) Troubleshooting#
    • <h2> 9) PR checklist#
    • <h2> 10) Useful links#
160/nemo/megatron-bridge/latest/adding-new-models.html
  • <h1> Parallelisms Guide#
    • <h2> Data Parallelism#
      • <h3> Distributed Data Parallelism#
      • <h3> Distributed Optimizer#
      • <h3> Enable Data Parallelism#
    • <h2> Model Parallelism#
      • <h3> Tensor Parallelism#
      • <h3> Pipeline Parallelism#
      • <h3> Expert Parallelism and Mixture of Experts (MoE)#
    • <h2> Activation Partitioning#
      • <h3> Sequence Parallelism#
      • <h3> Context Parallelism#
    • <h2> Combined Parallelism Example#
    • <h2> Data Parallel Size Calculation#
    • <h2> Strategy Selection Guide#
      • <h3> Dense Models by Size#
      • <h3> MoE Models#
      • <h3> By Hardware Topology#
      • <h3> By Sequence Length#
    • <h2> Configuration Guidelines#
      • <h3> Memory Optimization#
      • <h3> Performance Optimization#
      • <h3> Compatibility#
    • <h2> Related Artifacts#
    • <h2> Resources#
250/nemo/megatron-bridge/latest/parallelisms.html
  • <h1> Performance#
    • <h2> Nomenclature#
    • <h2> Performance Metrics#
    • <h2> Performance Summary for Large Language Models#
    • <h2> 26.02.01 NeMo Container#
      • <h3> Pre-Training Performance#
    • <h2> 26.02 NeMo Container#
      • <h3> Pre-Training Performance#
    • <h2> 25.11 NeMo Container#
      • <h3> Pre-Training Performance#
    • <h2> 25.09 NeMo Container#
      • <h3> Pre-Training Performance#
120/nemo/megatron-bridge/latest/performance-summary.html
  • <h1> Launch the NVIDIA NeMo Agent Toolkit API Server and User Interface#
    • <h2> User Interface Features#
    • <h2> Walk-through#
      • <h3> Prerequisites#
      • <h3> Start the NeMo Agent Toolkit Server#
      • <h3> Verify the NeMo Agent Toolkit Server is Running#
      • <h3> Launch the NeMo Agent Toolkit User Interface#
      • <h3> Connect the User Interface to the NeMo Agent Toolkit Server Using HTTP API#
      • <h3> Simple Calculator Example Conversation#
90/nemo/agent-toolkit/latest/run-workflows/launching-ui.html
  • <h1> Megatron Bridge Conversion Technical Details#
    • <h2> Architecture at a glance#
    • <h2> Conversion workflow#
      • <h3> HF → Megatron (import)#
      • <h3> Megatron → HF (export)#
    • <h2> Param mappings and parallelism#
      • <h3> Example Mapping - ColumnParallelMapping: PP, TP, EP in practice#
    • <h2> Architecture-specific bridge example: Qwen3#
80/nemo/megatron-bridge/latest/bridge-tech-details.html
  • <h1> Documentation Development#
    • <h2> Build the Documentation#
    • <h2> Live Building#
    • <h2> Write Tests in Python Docstrings#
    • <h2> Run Tests in Python Docstrings#
    • <h2> Documentation Version#
      • <h3> versions1.json#
    • <h2> project.json#
    • <h2> conf.py#
90/nemo/megatron-bridge/latest/documentation.html
  • <h1> NeMo Agent Toolkit as an MCP Server#
    • <h2> Decision#
    • <h2> Installation#
    • <h2> MCP Server Usage#
      • <h3> Filtering MCP Tools#
      • <h3> Mounting at Custom Paths#
    • <h2> Displaying MCP Tools published by an MCP server#
      • <h3> Using the nat mcp client command#
      • <h3> Using the /debug/tools/list route (no MCP client required)#
    • <h2> Integration with MCP Clients#
      • <h3> Example#
    • <h2> Verifying MCP Server Health#
      • <h3> Using the /health route#
      • <h3> Using the nat mcp client ping command#
    • <h2> Security Considerations#
      • <h3> Authentication Limitations#
      • <h3> Local Development#
      • <h3> Production Deployment#
180/nemo/agent-toolkit/latest/run-workflows/mcp-server.html
  • <h1> Get Started with 🤗 Hugging Face Conversion#
    • <h2> Design and Goals#
    • <h2> Loading a 🤗 Hugging Face Model into Megatron#
      • <h3> Accessing Gated 🤗 Hugging Face Models#
      • <h3> Basic Usage#
      • <h3> Advanced Loading Options#
      • <h3> Using Model Providers#
    • <h2> Check Supported Models#
    • <h2> Converting Back to 🤗 Hugging Face#
    • <h2> Common Patterns and Best Practices#
      • <h3> 1. Always Use High-Level APIs#
      • <h3> 2. Configure Before Creating Models#
      • <h3> 3. Leverage the Parameter Streaming API#
      • <h3> 4. Use from_hf_pretrained for Export Workflows#
    • <h2> Convenience Workflows (Commands)#
      • <h3> HF → Megatron checkpoint import (one call)#
      • <h3> Megatron → HF export (one call)#
      • <h3> Create Megatron models and run locally#
      • <h3> Launch with multiple GPUs (example)#
    • <h2> AutoBridge API Reference#
200/nemo/megatron-bridge/latest/bridge-guide.html
  • <h1> NVIDIA NeMo Agent Toolkit Workflow as an A2A Client#
    • <h2> Installation#
    • <h2> A2A Client Configuration#
      • <h3> Basic Configuration#
      • <h3> Configuration Options#
      • <h3> Multiple A2A Clients#
    • <h2> Three-Level API Architecture#
      • <h3> Level 1: High-Level API (Recommended)#
      • <h3> Level 2: Helper Functions#
      • <h3> Level 3: Low-Level Protocol API#
    • <h2> Advanced: Understanding Agent Card Discovery#
    • <h2> Transport Support#
    • <h2> Streaming Support#
    • <h2> Examples#
    • <h2> CLI Utilities#
      • <h3> Discover Agent#
      • <h3> Call Agent#
    • <h2> Troubleshooting#
      • <h3> Connection Issues#
      • <h3> Performance Issues#
    • <h2> Protocol Compliance#
    • <h2> Related Documentation#
220/nemo/agent-toolkit/latest/build-workflows/a2a-client.html
  • <h1> About Building NVIDIA NeMo Agent Toolkit Workflows#
    • <h2> Understanding the Workflow Configuration File#
    • <h2> Using Agents With Workflows#
    • <h2> Using Control Flow Components With Workflows#
40/nemo/agent-toolkit/latest/build-workflows/about-building-workflows.html
  • <h1> Migration Guide#
    • <h2> Migrating to a new version of NeMo Agent Toolkit#
    • <h2> Version Specific Changes#
      • <h3> v1.5.0#
      • <h3> v1.4.0#
      • <h3> v1.3.0#
      • <h3> v1.2.0#
      • <h3> v1.1.0#
80/nemo/agent-toolkit/latest/resources/migration-guide.html
  • <h1> NVIDIA NeMo Agent Toolkit Workflow as an A2A Server#
    • <h2> Installation#
    • <h2> Basic Usage#
      • <h3> Starting an A2A Server#
      • <h3> Server Options#
      • <h3> Configuration File Approach#
      • <h3> Concurrency Control#
      • <h3> Additional Configuration Options#
      • <h3> Kubernetes and Ingress Deployments#
    • <h2> How Workflows Map to A2A Agents#
      • <h3> Example Mapping#
      • <h3> Viewing the Agent Card#
      • <h3> Invoking the Agent with the CLI#
    • <h2> Examples#
    • <h2> Troubleshooting#
      • <h3> Server Won’t Start#
    • <h2> Security Considerations#
      • <h3> Authentication#
      • <h3> Best Practices#
    • <h2> Protocol Compliance#
    • <h2> Related Documentation#
210/nemo/agent-toolkit/latest/run-workflows/a2a-server.html
  • <h1> Size a GPU Cluster With NVIDIA NeMo Agent Toolkit#
    • <h2> Prerequisites#
    • <h2> Overview#
    • <h2> Getting Started With Sizing a GPU Cluster#
      • <h3> Step 1: Gather Metrics#
      • <h3> Step 2: Estimate GPU Cluster Size#
    • <h2> Details#
      • <h3> Gather Metrics#
      • <h3> Dataset Requirements#
      • <h3> Specifying the Concurrency Range#
      • <h3> Sample Output#
      • <h3> Using a Remote Workflow#
      • <h3> Handling Failed Workflows#
      • <h3> Estimate GPU Cluster Size#
      • <h3> Target and Test Parameters#
      • <h3> Slope-based Estimation#
      • <h3> Programmatic Usage#
170/nemo/agent-toolkit/latest/improve-workflows/sizing-calc.html
  • <h1> Test Time Compute With NVIDIA NeMo Agent Toolkit#
    • <h2> Core Design#
      • <h3> Strategy pipeline#
      • <h3> StrategyBase#
      • <h3> TTCItem#
    • <h2> Built‑in Strategies#
    • <h2> Pre‑Built TTC Functions#
    • <h2> Creating and Registering a New Strategy#
    • <h2> Composing Strategies in a Config#
    • <h2> Extending Tools and Pipelines#
    • <h2> Testing your strategy#
110/nemo/agent-toolkit/latest/improve-workflows/test-time-compute.html
  • <h1> NVIDIA NeMo Agent Toolkit Optimizer#
    • <h2> Introduction#
      • <h3> What is Parameter Optimization?#
      • <h3> Why Use Parameter Optimization?#
      • <h3> Real-World Example#
      • <h3> What This Guide Covers#
    • <h2> How it Works#
    • <h2> Core Concepts: OptimizableField and SearchSpace#
      • <h3> Understanding OptimizableField#
      • <h3> Understanding SearchSpaces#
      • <h3> Loading Prompts from Files#
      • <h3> How They Work Together#
    • <h2> Implementing OptimizableField#
      • <h3> SearchSpace Model#
      • <h3> OptimizableField Function#
    • <h2> Enabling Optimization in Configuration Files#
      • <h3> Overriding Search Spaces in Configuration Files#
    • <h2> Default Optimizable LLM Parameters#
    • <h2> Optimizer Configuration#
      • <h3> OptimizerConfig#
      • <h3> OptimizerMetric#
      • <h3> How Genetic Prompt Optimization Works in Practice#
      • <h3> Key GA Concepts#
    • <h2> Prompt Optimization with Genetic Algorithm (GA)#
      • <h3> Workflow#
      • <h3> Oracle Feedback Configuration#
      • <h3> Outputs#
    • <h2> Running the Optimizer#
      • <h3> CLI Command#
      • <h3> Options#
    • <h2> Understanding the Output#
      • <h3> Understanding the Pareto Visualizations#
      • <h3> Selecting the Best Configuration#
    • <h2> Optimization Callbacks#
      • <h3> OptimizerCallback Protocol#
      • <h3> Registration#
      • <h3> Built-in Implementation#
    • <h2> A Complete Example of Optimization#
    • <h2> Best Practices and Tuning Guide#
      • <h3> Choosing Optimizer Parameters#
      • <h3> Interpreting Optimization Results#
      • <h3> Common Pitfalls and Solutions#
      • <h3> Multi-Objective Optimization Strategies#
      • <h3> Workflow-Specific Tips#
      • <h3> Advanced Techniques#
450/nemo/agent-toolkit/latest/improve-workflows/optimizer.html
  • <h1> NVIDIA NeMo Agent Toolkit Troubleshooting#
    • <h2> Workflow Issues#
    • <h2> Runtime Issues#
    • <h2> Dependency Issues#
40/nemo/agent-toolkit/latest/resources/troubleshooting.html
  • <h1> NVIDIA NeMo Agent Toolkit as an MCP Server using FastMCP#
    • <h2> Decision#
    • <h2> Installation#
    • <h2> FastMCP Server Usage#
      • <h3> Using Developer Mode#
      • <h3> Generating MCP Client Configuration Snippets#
      • <h3> Filtering FastMCP Tools#
      • <h3> Mounting at Custom Paths#
    • <h2> Inspecting and Running MCP Tools Published by a FastMCP Server#
      • <h3> List all tools#
      • <h3> List a tool with schema#
      • <h3> Call a tool with JSON arguments#
      • <h3> Using the /debug/tools/list route (no MCP client required)#
    • <h2> Integration with MCP Clients#
    • <h2> Authentication#
    • <h2> Verifying FastMCP Server Health#
    • <h2> Related Examples#
170/nemo/agent-toolkit/latest/run-workflows/fastmcp-server.html
  • <h1> Workflow Configuration#
    • <h2> Configuration Object#
    • <h2> Workflow Configuration File#
      • <h3> functions#
      • <h3> llms#
      • <h3> embedders#
      • <h3> workflow#
      • <h3> general#
      • <h3> eval#
      • <h3> memory#
      • <h3> retrievers#
      • <h3> Environment Variable Interpolation#
      • <h3> Configuration Inheritance#
      • <h3> Loading Content from Files#
140/nemo/agent-toolkit/latest/build-workflows/workflow-configuration.html
  • <h1> Plugin System in NVIDIA NeMo Agent Toolkit#
    • <h2> Supported Plugin Types#
    • <h2> Anatomy of a Plugin#
      • <h3> Decorators#
      • <h3> Entry Point#
      • <h3> CLI Command Plugins#
60/nemo/agent-toolkit/latest/extend/plugins.html
  • <h1> Embedders in NVIDIA NeMo Agent Toolkit#
    • <h2> Supported Embedder Providers#
    • <h2> Embedder Configuration#
      • <h3> NVIDIA NIM#
      • <h3> OpenAI#
      • <h3> Azure OpenAI#
      • <h3> Hugging Face#
70/nemo/agent-toolkit/latest/build-workflows/embedders.html
  • <h1> NVIDIA NeMo Agent Toolkit as an MCP Client#
    • <h2> Installation#
    • <h2> Accessing Protected MCP Servers#
    • <h2> MCP Client Configuration#
      • <h3> mcp_client Configuration#
    • <h2> Transport Configuration#
      • <h3> Transport Types#
      • <h3> Streamable-HTTP Mode Configuration#
      • <h3> SSE Mode Configuration#
      • <h3> STDIO Mode Configuration#
    • <h2> Example#
    • <h2> Displaying MCP Tools using the CLI#
      • <h3> List All Tools#
      • <h3> Get Tool Details#
      • <h3> Call a Tool#
      • <h3> Using Protected MCP Servers#
    • <h2> List MCP Client Tools using the HTTP endpoint#
      • <h3> Steps#
      • <h3> Endpoint#
      • <h3> Sample Output#
      • <h3> Per-user endpoint#
    • <h2> MCP Inspection via UI#
      • <h3> Steps#
      • <h3> Sample Output#
      • <h3> Troubleshooting#
250/nemo/agent-toolkit/latest/build-workflows/mcp-client.html
  • <h1> Install NVIDIA NeMo Agent Toolkit#
    • <h2> Supported LLM APIs#
    • <h2> Packages#
    • <h2> Other Extras#
    • <h2> Supported Platforms#
    • <h2> Software Prerequisites#
      • <h3> Additional Prerequisites for Development#
    • <h2> Install from Package#
    • <h2> Install From Source#
    • <h2> Next Steps#
100/nemo/agent-toolkit/latest/get-started/installation.html
  • <h1> Retrievers in NVIDIA NeMo Agent Toolkit#
    • <h2> Features#
    • <h2> Included Retriever Providers#
    • <h2> Retriever Configuration#
      • <h3> NVIDIA NIM#
      • <h3> Milvus#
      • <h3> Configuration Examples#
      • <h3> Developing with Retrievers#
80/nemo/agent-toolkit/latest/build-workflows/retrievers.html
  • <h1> Sharing NVIDIA NeMo Agent Toolkit Components#
    • <h2> Enabling Local and Remote Discovery#
    • <h2> Package Distribution#
      • <h3> Building a Wheel Package#
      • <h3> Publish to a Remote Registry#
      • <h3> Share Source Code#
    • <h2> Summary#
70/nemo/agent-toolkit/latest/components/sharing-components.html
  • <h1> About Running NVIDIA NeMo Agent Toolkit Workflows#
    • <h2> Prerequisites#
      • <h3> Set Up API Keys#
    • <h2> Using the nat run Command#
    • <h2> Using the nat serve Command#
    • <h2> Using the nat mcp serve Command#
    • <h2> Using the nat fastmcp server run Command#
    • <h2> Using the nat eval Command#
    • <h2> Using the Python API#
90/nemo/agent-toolkit/latest/run-workflows/about-running-workflows.html
  • <h1> Security Considerations#
    • <h2> Overview#
    • <h2> What to Be Aware Of#
      • <h3> Tool Abuse and Misuse#
      • <h3> Loss of System Integrity#
      • <h3> Loss of Confidentiality#
      • <h3> Logging and Observability Security Considerations#
      • <h3> Supply Chain and Third Party Security Aspects#
    • <h2> Example Security Approaches#
    • <h2> References#
100/nemo/agent-toolkit/latest/resources/security-considerations.html
  • <h1> Support#
10/nemo/agent-toolkit/latest/resources/support.html
  • <h1> Agent Evaluation in NVIDIA NeMo Agent Toolkit#
    • <h2> Prerequisites#
    • <h2> Evaluating a Workflow#
    • <h2> Understanding the Evaluation Configuration#
    • <h2> Evaluation outputs (what you will get)#
      • <h3> Workflow outputs (always available)#
      • <h3> Configuration outputs (always available)#
      • <h3> Evaluator outputs (only when configured)#
      • <h3> Profiler and observability outputs (only when profiler is enabled)#
    • <h2> Understanding the Dataset Format#
    • <h2> Understanding the Evaluator Configuration#
      • <h3> Display all evaluators#
      • <h3> Ragas Evaluator#
      • <h3> Trajectory Evaluator#
    • <h2> Summary Output#
    • <h2> Workflow Output#
    • <h2> Evaluator Output#
    • <h2> Visualizing Evaluation Results#
      • <h3> Step 1: Install the Weave plugin#
      • <h3> Step 2: Enable logging to Weave in the configuration file#
      • <h3> Step 3: Run evaluation using the configuration file#
      • <h3> Step 4: View evaluation results in Weave dashboard#
    • <h2> Evaluation Callbacks#
      • <h3> EvalCallback Protocol#
      • <h3> Registration#
      • <h3> Built-in Implementation#
    • <h2> Evaluating Remote Workflows#
    • <h2> Evaluation Endpoint#
    • <h2> Adding Custom Evaluators#
    • <h2> Adding Custom Dataset Loaders#
    • <h2> Overriding Evaluation Configuration#
    • <h2> Evaluation Details#
      • <h3> Using Datasets#
      • <h3> NeMo Agent Toolkit Built-in Evaluators#
      • <h3> Adding Custom Evaluators#
      • <h3> Running multiple repetitions#
      • <h3> Running evaluation on large datasets#
      • <h3> Pickup where you left off#
      • <h3> Running evaluation offline#
      • <h3> Running the workflow over a dataset without evaluation#
      • <h3> Evaluation output#
      • <h3> Workflow Output Intermediate Step Filtering#
      • <h3> Customizing the output#
      • <h3> Remote Storage#
      • <h3> Profiling and Performance Monitoring of NeMo Agent Toolkit Workflows#
450/nemo/agent-toolkit/latest/improve-workflows/evaluate.html
  • <h1> NVIDIA NeMo Agent Toolkit FAQs#
    • <h2> Do I Need to Rewrite All of my Existing Code to Use NeMo Agent Toolkit?#
    • <h2> Is NeMo Agent Toolkit another LLM or Agentic Framework?#
    • <h2> Is NeMo Agent Toolkit An Attempt to Solve Agent-to-Agent Communication?#
    • <h2> Is NeMo Agent Toolkit an Observability Platform?#
50/nemo/agent-toolkit/latest/resources/faq.html
  • <h1> Quick Start with NVIDIA NeMo Agent Toolkit#
    • <h2> Obtaining API Keys#
      • <h3> Optional OpenAI API Key#
    • <h2> Running Example Workflows#
      • <h3> Running the Simple Workflow#
    • <h2> NeMo Agent Toolkit Packages#
    • <h2> Next Steps#
70/nemo/agent-toolkit/latest/get-started/quick-start.html
  • <h1> Command Line Interface#
    • <h2> Overview#
    • <h2> A2A#
      • <h3> Serve#
      • <h3> Client#
    • <h2> Start#
      • <h3> FastAPI#
      • <h3> Console#
    • <h2> MCP#
      • <h3> Client#
      • <h3> Serve#
    • <h2> FastMCP#
      • <h3> Server Commands#
    • <h2> Run#
    • <h2> Serve#
    • <h2> Evaluation#
    • <h2> Finetune#
      • <h3> Options Description#
      • <h3> Examples#
    • <h2> Optimize#
      • <h3> Options Description#
    • <h2> GPU Cluster Sizing#
      • <h3> Examples#
    • <h2> Uninstall#
    • <h2> Validate#
    • <h2> Workflow#
      • <h3> Create#
      • <h3> Reinstall#
      • <h3> Delete#
    • <h2> Information Commands#
      • <h3> Components Information#
      • <h3> Channels Information#
    • <h2> Configuration Commands#
      • <h3> Remote Registry Configuration#
    • <h2> Remote Registry Interactions#
      • <h3> Publishing NeMo Agent Toolkit Components#
      • <h3> Discovering NeMo Agent Toolkit Components#
      • <h3> Pulling in NeMo Agent Toolkit Components#
      • <h3> Removing NeMo Agent Toolkit Components#
    • <h2> Object Store Commands#
      • <h3> MySQL Object Store#
      • <h3> Redis Object Store#
      • <h3> S3 Object Store#
      • <h3> Operations#
440/nemo/agent-toolkit/latest/reference/cli.html
  • <h1> Profiling and Performance Monitoring of NVIDIA NeMo Agent Toolkit Workflows#
    • <h2> Prerequisites#
    • <h2> Current Profiler Architecture#
      • <h3> Profiler Decorators and Callbacks#
      • <h3> Profiler Runner#
      • <h3> CLI Integrations#
    • <h2> Using the Profiler#
      • <h3> Step 1: Enabling Instrumentation on a Workflow [Optional]#
      • <h3> Step 2: Configuring the Profiler with Eval#
      • <h3> Step 3: Running the Profiler#
    • <h2> Prediction Trie and Dynamo Routing Hints#
      • <h3> What the Prediction Trie Captures#
      • <h3> Auto Latency Sensitivity#
      • <h3> Enabling the Prediction Trie#
      • <h3> Using the Prediction Trie at Runtime#
      • <h3> Manual Latency Sensitivity#
    • <h2> Walkthrough of Profiling a Workflow#
      • <h3> Defining a Workflow#
      • <h3> Configuring the Workflow#
      • <h3> Running the Profiler#
      • <h3> Analyzing the Profiling Results#
      • <h3> Plotting Prompt vs Completion Tokens for LLMs#
      • <h3> Analyzing Workflow Runtimes#
      • <h3> Analyzing Token Efficiency#
      • <h3> Understanding Where the Models Spend Time#
      • <h3> Analyzing Ragas Metrics#
      • <h3> Conclusion#
    • <h2> Providing Feedback#
280/nemo/agent-toolkit/latest/improve-workflows/profiler.html
  • <h1> NVIDIA NeMo Agent Toolkit Release Notes#
    • <h2> Release 1.5.0#
      • <h3> Summary#
    • <h2> Known Issues#
40/nemo/agent-toolkit/latest/release-notes.html
  • <h1> Memory in NVIDIA NeMo Agent Toolkit#
    • <h2> Included Memory Modules#
    • <h2> Automatic Memory Wrapper Agent#
      • <h3> Why Use Automatic Memory?#
      • <h3> Quick Start#
      • <h3> Configuration Options#
      • <h3> Multi-Tenant Memory Isolation#
    • <h2> Examples#
    • <h2> Additional Resources#
90/nemo/agent-toolkit/latest/build-workflows/memory.html
  • <h1> API Reference#
10/nemo/agent-toolkit/latest/api/index.html
  • <h1> NVIDIA NeMo Retriever
    • <h2> NeMo Retriever
20/nemo/retriever/
  • <h1> Object Stores in NVIDIA NeMo Agent Toolkit#
    • <h2> Features#
    • <h2> Core Components#
      • <h3> ObjectStoreItem#
      • <h3> ObjectStore Interface#
    • <h2> Included Object Stores#
    • <h2> Usage#
      • <h3> Configuration#
      • <h3> Using Object Stores in Functions#
      • <h3> File Server Integration#
    • <h2> Examples#
    • <h2> Error Handling#
    • <h2> Additional Resources#
130/nemo/agent-toolkit/latest/build-workflows/object-store.html
  • <h1> About Improving NVIDIA NeMo Agent Toolkit Workflows#
10/nemo/agent-toolkit/latest/improve-workflows/about-improving-workflows.html
  • <h1> Troubleshooting#
    • <h2> Nested AsyncIO Loop#
20/nemo/guardrails/latest/troubleshooting.html
  • <h1> API Reference#
10/nemo/export-deploy/latest/apidocs/index.html
  • <h1> Export and Deploy Large Language Models#
    • <h2> Overview#
    • <h2> Supported Model/Checkpoint Formats#
      • <h3> NeMo 2.0 Model/Checkpoints#
      • <h3> Megatron Bridge Model/Checkpoints#
      • <h3> AutoModel Model/Checkpoints#
      • <h3> Megatron-LM Model/Checkpoints#
70/nemo/export-deploy/latest/llm/index.html
  • <h1> Documentation Development#
    • <h2> Build the Documentation#
    • <h2> Live Building#
    • <h2> Documentation Version#
40/nemo/export-deploy/latest/documentation.html
  • <h1> Training Tutorials#
    • <h2> RL (GRPO)#
      • <h3> Multi-Environment Training#
    • <h2> SFT & DPO#
40/nemo/gym/latest/training-tutorials/index.html
  • <h1> Test NeMo Export-Deploy#
    • <h2> Unit Tests#
    • <h2> Functional Tests#
30/nemo/export-deploy/latest/testing.html
  • <h1> About NVIDIA NeMo Gym#
    • <h2> Motivation#
    • <h2> NeMo Gym#
30/nemo/gym/latest/about/index.html
  • <h1> Export and Deploy Multimodal Models#
    • <h2> Overview#
    • <h2> Supported Model/Checkpoint Formats#
      • <h3> NeMo 2.0 Model/Checkpoints#
      • <h3> Megatron Bridge Model/Checkpoints#
      • <h3> AutoModel Model/Checkpoints#
60/nemo/export-deploy/latest/mm/index.html
  • <h1> Multi-Step Environment#
    • <h2> What You’ll Build#
      • <h3> Episode Flow#
    • <h2> Implementation#
      • <h3> Key Insight#
    • <h2> Rollout Transcript#
60/nemo/gym/latest/environment-tutorials/multi-step-environment.html
  • <h1> Infrastructure#
10/nemo/gym/latest/infrastructure/index.html
  • <h1> Nemotron 3 Nano 30B#
    • <h2> Prerequisites#
    • <h2> 1. Initial Setup#
      • <h3> 1.1 Set Workspace Directory#
      • <h3> 1.2 Clone the Repository#
      • <h3> 1.3 Prepare Container Image#
      • <h3> 1.4 Install uv Tool#
      • <h3> 1.5 Download and Process Training Data#
      • <h3> 1.6 Download Model#
      • <h3> 1.7 Verify Setup#
    • <h2> 2. Create Launch Script#
    • <h2> 3. Submit Training Job#
    • <h2> 4. Monitor Job Status#
    • <h2> 5. Monitor Training Progress#
      • <h3> 5.1 Check Ray Cluster Logs#
      • <h3> 5.2 Verify Ray Cluster Formation#
      • <h3> 5.3 Watch Training Metrics#
    • <h2> 6. Troubleshooting#
      • <h3> Issue: Job Stays in Pending (PD) State#
      • <h3> Issue: Ray Head Doesn’t Start#
      • <h3> Issue: Training Crashes with Cache Errors#
    • <h2> 7. Key Technical Details#
      • <h3> Why Ray.sub?#
      • <h3> Why Shared Cache?#
    • <h2> 8. File Structure Reference#
    • <h2> Next Steps#
260/nemo/gym/latest/model-recipes/nemotron-3-nano.html
  • <h1> Prepare and Validate Data#
    • <h2> Quick Start#
    • <h2> Data Format#
      • <h3> Minimal Format#
      • <h3> With Verification Fields#
      • <h3> Key Properties#
      • <h3> Message Roles#
    • <h2> Preprocess Raw Datasets#
      • <h3> Add responses_create_params#
      • <h3> Create Config for Custom Data#
    • <h2> Validation Modes#
      • <h3> Example Validation#
      • <h3> Training Preparation#
      • <h3> CLI Parameters#
    • <h2> Troubleshooting#
    • <h2> Validation Process#
      • <h3> Output Locations#
      • <h3> Re-Running#
      • <h3> Generated Metrics#
    • <h2> Dataset Configuration#
    • <h2> Next Steps#
210/nemo/gym/latest/data/prepare-validate.html
  • <h1> RL Environment Ecosystem#
    • <h2> Training Framework Integrations#
    • <h2> Environment Library Integrations#
    • <h2> Related NeMo Libraries#
40/nemo/gym/latest/about/ecosystem.html
  • <h1> Real-World Environment (Workplace Assistant)#
10/nemo/gym/latest/environment-tutorials/real-world-environment.html
  • <h1> Quickstart#
    • <h2> Before You Start#
    • <h2> Quickstart#
    • <h2> Next Steps#
40/nemo/gym/latest/get-started/index.html
  • <h1> Data#
    • <h2> Prerequisites#
    • <h2> Data Format#
      • <h3> Required Fields#
      • <h3> Optional Fields#
      • <h3> The agent_ref Field#
      • <h3> Example Data#
    • <h2> Quick Start#
    • <h2> Dataset Types#
    • <h2> Configuration#
      • <h3> Valid Licenses#
    • <h2> Workflow#
    • <h2> Validation Modes#
    • <h2> Common Errors#
    • <h2> Guides#
    • <h2> CLI Commands#
    • <h2> Large Datasets#
170/nemo/gym/latest/data/index.html
  • <h1> Multi-Environment Training#
    • <h2> Why Train on Multiple Environments?#
    • <h2> How to Configure#
    • <h2> Dataset Preparation#
    • <h2> Rollout Collection#
50/nemo/gym/latest/training-tutorials/multi-environment-training.html
  • <h1> Building Environments#
    • <h2> Tutorials#
    • <h2> Environment Properties#
      • <h3> Rollout Structure#
      • <h3> Core Capabilities#
50/nemo/gym/latest/environment-tutorials/index.html
  • <h1> RL Training with Unsloth#
    • <h2> Prerequisites#
    • <h2> Getting Started#
30/nemo/gym/latest/training-tutorials/unsloth.html
  • <h1> API Reference#
10/nemo/gym/latest/apidocs/index.html
  • <h1> Adding a benchmark to Gym#
    • <h2> Reward profiling#
    • <h2> Best practices#
30/nemo/gym/latest/environment-tutorials/adding-a-benchmark.html
  • <h1> Designing a customer evaluation benchmark#
    • <h2> Guiding Principles#
    • <h2> Functional Tips#
30/nemo/gym/latest/environment-tutorials/designing-customer-evaluation.html
  • <h1> Deployment Topology#
    • <h2> Training Framework Deployment#
      • <h3> Resource Requirements#
      • <h3> Cluster Co-location Strategy#
      • <h3> Choosing a Deployment Strategy#
    • <h2> Related Guides#
60/nemo/gym/latest/infrastructure/deployment-topology.html
  • <h1> Configuration Errors#
    • <h2> Startup Errors#
      • <h3> Missing Mandatory Value#
      • <h3> Server Reference Not Found#
    • <h2> Validation Errors#
      • <h3> Almost-Servers Detected#
60/nemo/gym/latest/troubleshooting/configuration.html
  • <h1> vLLM Model Server#
    • <h2> Use VLLMModel#
      • <h3> Install vLLM#
      • <h3> Download the model#
      • <h3> Spin up a vLLM server#
      • <h3> Configure NeMo Gym to use the local vLLM server#
      • <h3> Run rollout collection#
    • <h2> VLLMModel configuration reference#
      • <h3> Advanced: chat_template_kwargs#
      • <h3> Advanced: extra_body#
    • <h2> Use VLLMModel with multiple replicas of a model endpoint#
    • <h2> Training vs Offline Inference#
120/nemo/gym/latest/model-server/vllm.html
  • <h1> Detailed Setup Guide#
    • <h2> Requirements#
      • <h3> Hardware Requirements#
      • <h3> Software Requirements#
      • <h3> Additional Requirements#
      • <h3> Verified Configurations#
    • <h2> Prerequisites#
    • <h2> 1. Clone and Install#
    • <h2> 2. Configure Your API Key#
    • <h2> 3. Start the Servers#
    • <h2> 4. Test the Setup#
    • <h2> File Structure After Setup#
    • <h2> Next Steps#
130/nemo/gym/latest/get-started/detailed-setup.html
  • <h1> Offline Training with Rollouts (SFT/DPO) - Experimental#
    • <h2> Prerequisites#
    • <h2> Why Offline Training?#
    • <h2> Training Data Types#
      • <h3> Supervised Fine-Tuning (SFT) Data#
      • <h3> Direct Preference Optimization (DPO) Data#
    • <h2> Data Preparation Overview#
    • <h2> Step 1: Quality Filtering and Curation#
      • <h3> Automatic Filtering#
      • <h3> Manual Curation (Optional)#
    • <h2> Step 2: Format for Training#
      • <h3> SFT Data Processing#
      • <h3> DPO Data Processing#
    • <h2> Training Integration#
      • <h3> Standard Data Formats#
    • <h2> Validation and Evaluation#
      • <h3> Pre-Training Validation#
      • <h3> Post-Training Evaluation#
    • <h2> Best Practices#
      • <h3> 1. Data Quality Over Quantity#
      • <h3> 2. Balanced Datasets#
      • <h3> 3. Iterative Improvement#
      • <h3> 4. Version Control#
    • <h2> Troubleshooting#
      • <h3> Problem: Poor Training Data Quality#
      • <h3> Problem: Insufficient Data Diversity#
      • <h3> Problem: Training Instability#
    • <h2> What You’ve Learned#
    • <h2> Next Steps#
290/nemo/gym/latest/training-tutorials/offline-training-w-rollouts.html
  • <h1> Development Setup#
    • <h2> Quick Start#
    • <h2> Development Commands#
    • <h2> CI/CD Requirements#
      • <h3> Build Docs CI Failures#
      • <h3> Copyright Header Errors#
    • <h2> DCO and Commit Signing#
      • <h3> Quick Setup#
      • <h3> IDE Integration#
      • <h3> Making Signed Commits#
      • <h3> Troubleshooting#
      • <h3> Alternative: GPG Signing#
    • <h2> Common Issues#
      • <h3> Testing Issues#
      • <h3> Pre-commit Hook Failures#
    • <h2> Development Workflow#
160/nemo/gym/latest/contribute/development-setup.html
  • <h1> RL Framework Compatibility#
    • <h2> NeMo RL Container#
    • <h2> Unsloth#
30/nemo/gym/latest/reference/rl-framework-compatibility.html
  • <h1> Model Server#
    • <h2> Backend Guides#
    • <h2> Server Configuration#
30/nemo/gym/latest/model-server/index.html
  • <h1> Nemotron 3 Super#
10/nemo/gym/latest/model-recipes/nemotron-3-super.html
  • <h1> CLI Commands#
    • <h2> Quick Reference#
    • <h2> Server Management#
      • <h3> ng_run / nemo_gym_run#
      • <h3> ng_test / nemo_gym_test#
      • <h3> ng_test_all / nemo_gym_test_all#
      • <h3> ng_dev_test / nemo_gym_dev_test#
      • <h3> ng_init_resources_server / nemo_gym_init_resources_server#
    • <h2> Data Collection#
      • <h3> ng_collect_rollouts / nemo_gym_collect_rollouts#
      • <h3> ng_e2e_collect_rollouts / nemo_gym_e2e_collect_rollouts#
      • <h3> ng_reward_profile / nemo_gym_reward_profile#
    • <h2> Data Management#
      • <h3> ng_prepare_data / nemo_gym_prepare_data#
    • <h2> Dataset Registry - GitLab#
      • <h3> ng_upload_dataset_to_gitlab / nemo_gym_upload_dataset_to_gitlab#
      • <h3> ng_download_dataset_from_gitlab / nemo_gym_download_dataset_from_gitlab#
      • <h3> ng_delete_dataset_from_gitlab / nemo_gym_delete_dataset_from_gitlab#
    • <h2> Dataset Registry - HuggingFace#
      • <h3> ng_upload_dataset_to_hf / nemo_gym_upload_dataset_to_hf#
      • <h3> ng_download_dataset_from_hf / nemo_gym_download_dataset_from_hf#
      • <h3> ng_gitlab_to_hf_dataset / nemo_gym_gitlab_to_hf_dataset#
    • <h2> Configuration & Help#
      • <h3> ng_dump_config / nemo_gym_dump_config#
      • <h3> ng_help / nemo_gym_help#
      • <h3> ng_version / nemo_gym_version#
      • <h3> ng_pip_list / nemo_gym_pip_list#
      • <h3> ng_status / nemo_gym_status#
    • <h2> Getting Help#
    • <h2> Re-install Gym and dependencies#
300/nemo/gym/latest/reference/cli-commands.html
  • <h1> Agent Server#
    • <h2> Rollout Lifecycle#
    • <h2> Integrate Existing Agents#
      • <h3> Tools in Agent vs. Resources Server#
    • <h2> Server Configuration#
50/nemo/gym/latest/agent-server/index.html
  • <h1> Contribute to NeMo Gym#
    • <h2> Ways to Contribute#
    • <h2> Before You Start#
30/nemo/gym/latest/contribute/index.html
  • <h1> Rollout Collection#
    • <h2> Prerequisites#
    • <h2> 1. Inspect the Data#
    • <h2> 2. Verify Servers Are Running#
    • <h2> 3. Generate Rollouts#
    • <h2> 4. View Rollouts#
    • <h2> Rollout Generation Parameters#
    • <h2> Next Steps#
80/nemo/gym/latest/get-started/rollout-collection.html
  • <h1> Model Recipes#
    • <h2> Backend Guides#
20/nemo/gym/latest/model-recipes/index.html
  • <h1> Resources Server Implementation#
    • <h2> Episode Flow#
    • <h2> Implementation#
      • <h3> Key Pattern#
    • <h2> Rollout Transcript#
    • <h2> Verification: Trajectory Matching vs State Matching#
      • <h3> 1. Trajectory Matching (Sequence Matching)#
      • <h3> 2. State Matching (Outcome Matching)#
      • <h3> What Workplace Assistant Uses#
90/nemo/gym/latest/environment-tutorials/real-world-implementation.html
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301 /nemo-framework/user-guide/latest/nemotoolkit/features/optimizations/activation_recomputation.html/nemo/megatron-bridge/latest/training/activation-recomputation.html/nemo-framework/user-guide/latest/speech_ai/index.html
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301 /nemo-framework/user-guide/latest/nemotoolkit/features/optimizations/communication_overlap.html/nemo/megatron-bridge/latest/training/communication-overlap.html/nemo-framework/user-guide/latest/speech_ai/index.html
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Skipped URLs

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https://docs.aws.amazon.com/eks/latest/userguide/disaster-recovery-resiliency.html1/nemo/microservices/latest/set-up/manage-storage/backup-and-restore.html
https://docs.aws.amazon.com/eks/latest/userguide/efs-csi.html1/nemo/microservices/latest/set-up/manage-storage/pvc/aws.html
https://docs.aws.amazon.com/eks/latest/userguide/fsx-csi.html1/nemo/microservices/latest/set-up/manage-storage/pvc/aws.html
https://docs.cloud.google.com/memorystore/docs/redis/memorystore-for-redis-overview1/nemo/guardrails/latest/configure-rails/caching/model-memory-cache.html
https://docs.cursor.com/context/rules1/nemo/agent-toolkit/latest/resources/contributing/cursor/cursor-rules-developer-guide.html
https://docs.dask.org/en/stable/1/nemo/agent-toolkit/latest/reference/rest-api/api-server-endpoints.html
https://docs.databricks.com/aws/en/compute/configure1/nemo/automodel/latest/guides/llm/databricks.html
https://docs.databricks.com/aws/en/init-scripts/cluster-scoped1/nemo/automodel/latest/guides/llm/databricks.html
https://docs.databricks.com/aws/en/volumes/1/nemo/automodel/latest/guides/llm/databricks.html
https://docs.datadoghq.com/opentelemetry/interoperability/otlp_ingest_in_the_agent/?tab=host1/nim/llama-3-1-nemoguard-8b-contentsafety/latest/observability.html
https://docs.datadoghq.com/opentelemetry/setup/collector_exporter/1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.dbnl.com/1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.dbnl.com/get-started/quickstart1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.docker.com/compose/install/1/nemo/microservices/latest/generate-private-synthetic-data/docker-compose.html
https://docs.docker.com/compose/install/linux/1/nemo/microservices/latest/generate-private-synthetic-data/docker-compose.html
https://docs.docker.com/engine/install/1/nim/llama-3-1-nemoguard-8b-contentsafety/latest/getting-started.html
https://docs.docker.com/get-docker/1/nemo/agent-toolkit/latest/resources/contributing/testing/running-ci-locally.html
https://docs.docker.com/get-started/docker-concepts/running-containers/publishing-ports/1/nim/llama-3-1-nemoguard-8b-contentsafety/latest/configuration.html
https://docs.docker.com/get-started/get-docker/1/nemo/agent-toolkit/latest/components/functions/code-execution.html
https://docs.dynatrace.com/docs/analyze-explore-automate/distributed-tracing/distributed-tracing-app1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.dynatrace.com/docs/ingest-from/opentelemetry/collector1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.dynatrace.com/docs/shortlink/otel-collector-config1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.dynatrace.com/docs/shortlink/otel-getstarted-otlpexport1/nemo/agent-toolkit/latest/run-workflows/observe/observe.html
https://docs.fiddler.ai/product-guide/llm-monitoring/enrichments-private-preview1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/fiddler.html
https://docs.fiddler.ai/product-guide/llm-monitoring/guardrails1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/fiddler.html
https://docs.fiddler.ai/product-guide/llm-monitoring/llm-based-metrics1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/fiddler.html
https://docs.fiddler.ai/ui-guide/administration-ui/settings1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/fiddler.html
https://docs.langchain.com/langsmith/cli1/nemo/agent-toolkit/latest/run-workflows/existing-agents/langgraph.html
https://docs.langchain.com/langsmith/example-data-format1/nemo/agent-toolkit/latest/api/nat/plugins/langchain/dataset_loader/langsmith/index.html
https://docs.langchain.com/oss/python/integrations/chat1/nemo/guardrails/latest/about/supported-llms.html
https://docs.langchain.com/oss/python/langchain/overview1/nemo/agent-toolkit/latest/components/integrations/frameworks.html
https://docs.litellm.ai/docs/providers1/nemo/agent-toolkit/latest/build-workflows/llms/index.html
https://docs.ngc.nvidia.com/cli/cmd.html1/nemo/microservices/latest/generate-private-synthetic-data/docker-compose.html
https://docs.omniverse.nvidia.com/guide-sdg/latest/setup.html1/nemo/evaluator/latest/tutorials/local-evaluation-of-existing-endpoint.html
https://docs.patronus.ai/docs/quickstart-guide1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/patronus-evaluate-api.html
https://docs.patronus.ai/reference/evaluate_v1_evaluate_post1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/patronus-evaluate-api.html
https://docs.private-ai.com/?utm_medium=github&utm_campaign=nemo-guardrails1/nemo/guardrails/latest/configure-rails/guardrail-catalog/pii-detection.html
https://docs.private-ai.com/entities/?utm_medium=github&utm_campaign=nemo-guardrails1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/privateai.html
https://docs.private-ai.com/quickstart/?utm_medium=github&utm_campaign=nemo-guardrails1/nemo/guardrails/latest/configure-rails/guardrail-catalog/community/privateai.html
https://docs.pydantic.dev/2.11/1/nemo/agent-toolkit/latest/build-workflows/workflow-configuration.html
https://docs.pydantic.dev/latest/1/nemo/microservices/latest/design-synthetic-data-from-scratch-or-se…-columns/structured-outputs.html
https://docs.pydantic.dev/latest/api/base_model/1/nemo/microservices/latest/pysdk/index.html
https://docs.pytest.org/en/stable1/nemo/agent-toolkit/latest/resources/contributing/testing/running-tests.html
You have reached the hard limit of 200 rows as a protection against very large output or exhausted memory. You can change this with --rows-limit.
No rows found, please edit your search term.

TOP fastest URLs

Found 20 row(s).
Time 🔼StatusFast URL
20 ms 200 /nemo/run/latest/index.html
22 ms 200 /nemo/megatron-bridge/latest/index.html
22 ms 200 /nemo/index.html
22 ms 200 /nemo/microservices/latest/index.html
22 ms 200 /nemo/evaluator/latest/index.html
23 ms 200 /nemo/rl/latest/index.html
23 ms 200 /nemo/curator/latest/index.html
23 ms 200 /nemo/guardrails/latest/index.html
24 ms 200 /nemo-guardrails/index.html
34 ms 200 /nemo/agent-toolkit/latest/index.html
40 ms 200 /nemo/agent-toolkit/latest/run-workflows/launching-ui.html
40 ms 200 /nemo/guardrails/0.19.0/user-guides/configuration-guide/llm-configuration.html
40 ms 200 /nemo/gym/latest/model-server/index.html
40 ms 200 /nemo/microservices/latest/pysdk/index.html
41 ms 200 /nemo/gym/latest/troubleshooting/configuration.html
41 ms 200 /nemo/guardrails/latest/about/rail-types.html
41 ms 200 /nemo/rl/latest/about/algorithms/on-policy-distillation.html
41 ms 200 /nemo-framework/user-guide/latest/nemotoolkit/tts/magpietts-longform.html
41 ms 200 /nemo/guardrails/latest/configure-rails/colang/colang-1/tutorials/5-output-rails/README.html
42 ms 200 /nemo/guardrails/0.18.0/release-notes.html
No rows found, please edit your search term.

TOP slowest URLs

Found 20 row(s).
Time 🔽StatusSlow URL
2.9 s 200 /nemo/megatron-bridge/latest/apidocs/bridge/bridge.recipes.deepseek.html
1.5 s 200 /nemo/megatron-bridge/latest/skills/perf-techniques/packed-sequences-long-context/SKILL.html
1.4 s 200 /nemo/export-deploy/latest/apidocs/nemo_deploy/nemo_deploy.llm.trtllm_api_deployable.html
1.3 s 200 /nemo/export-deploy/latest/apidocs/nemo_deploy/nemo_deploy.service.html
1.3 s 200 /nemo/guardrails/0.14.0/colang-2/language-reference/csl/timing.html
1.2 s 200 /nemo/agent-toolkit/latest/api/nat/plugins/mysql/index.html
1.1 s 200 /nemo/guardrails/0.14.0/user-guides/multi-config-api/README.html
1.1 s 200 /nemo/agent-toolkit/latest/api/nat/utils/exception_handlers/schemas/index.html
1.1 s 200 /nemo/export-deploy/latest/apidocs/nemo_export/nemo_export.utils._mock_import.html
1.1 s 200 /nemo/agent-toolkit/latest/api/nat/plugins/adk/adk_parser/index.html
1.1 s 200 /nemo/agent-toolkit/latest/resources/security-considerations.html
1.1 s 200 /nemo/curator/latest/apidocs/stages/stages.synthetic.nemotron_cc.html
1.1 s 200 /nemo/guardrails/0.15.0/getting-started/7-rag/README.html
1.1 s 200 /nemo/agent-toolkit/latest/api/nat/plugins/a2a/cli/index.html
1 s 200 /nemo/gym/latest/_modules/nemo_gym/train_data_utils.html
1 s 200 /nemo/agent-toolkit/latest/api/nat/test/llm/index.html
1 s 200 /nemo/agent-toolkit/latest/api/nat/middleware/cache/cache_middleware_config/index.html
1 s 200 /nemo/agent-toolkit/latest/api/observability/processor/trace_conversion/adapter/register/index.html
1 s 200 /nemo/agent-toolkit/latest/api/nat/parameter_optimization/update_helpers/index.html
1 s 200 /nemo/agent-toolkit/latest/extend/testing/add-unit-tests-for-tools.html
No rows found, please edit your search term.

Content types

Content typeURLs 🔽Total sizeTotal timeAvg timeStatus 20xStatus 30xStatus 40x
HTML3574349 MB1882 s526 ms 3565 09
Redirect215 kB901 ms42 ms 021 0

Content types (MIME types)

Content typeURLs 🔽Total sizeTotal timeAvg timeStatus 20xStatus 30xStatus 40x
text / html2923317 MB1530 s523 ms 2902 21 0
text/html; charset=utf-866631 MB352 s529 ms 657 09
text/html;charset=UTF-86703 kB372 ms62 ms 6 00

Source domains

DomainTotalsHTMLRedirect
docs.nvidia.com3595 / 349MB / 1883s3574 / 349MB / 1882s21 / 5kB / 901ms

HTTP headers

Found 27 row(s).
Header 🔼OccursUniqueValues previewMin valueMax value
Accept-Ranges4101bytes
Akamai-Cache-Status35956[see values below]
Cache-Control35951no-store, no-cache, must-revalidate, max-age=0
Content-Length23-[ignored generic values]0 B77 kB
Content-Security-Policy35951img-src https://* data:; style-src-elem 'self' 'unsafe-inline' 'unsafe-eval' ht…ww.nvidia.com/ https://static.reo.dev/;
Content-Type35953text/html (2923) / text/html; charset=utf-8 (666) / text/html;charset=UTF-8 (6)
Country_code331c_code=FI; Path=/; Secure
Date3595-[ignored generic values]2026-03-242026-03-24
Edge-Cache-Tag35744[see values below]
Etag3568-[ignored generic values]
Expires3595-[ignored generic values]
Last-Modified3568-[ignored generic values]2025-05-142026-03-23
Location2119[see values below]
Pragma35951no-cache
Server35953AmazonS3 (3568) / AkamaiGHost (21) / istio-envoy (6)
Set-Cookie3595-[ignored generic values]
Strict-Transport-Security61max-age=31536000; includeSubDomains
Vary4121Accept-Encoding
X-Amz-Cf-Id356820+[see values below]
X-Amz-Cf-Pop35681HAM50-P2
X-Amz-Replication-Status35681COMPLETED
X-Amz-Server-Side-Encryption35681AES256
X-Amz-Version-Id356820+[see values below]
X-Envoy-Decorator-Operation61brightspot-frontend.nvidia-docs.svc.cluster.local:80/*
X-Envoy-Upstream-Service-Time6392 (2) / 77 (2) / 87 (2)
X-Nv-Aws-Origin35681CloudFront
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No rows found, please edit your search term.

HTTP header values

Found 91 row(s).
HeaderOccursValue
Accept-Ranges410bytes
Akamai-Cache-Status3076Miss from child, Miss from parent
Akamai-Cache-Status355Miss from child, Hit from parent
Akamai-Cache-Status119Miss from child, RefreshHit from parent
Akamai-Cache-Status21Redirect from child
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Cache-Control3595no-store, no-cache, must-revalidate, max-age=0
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Content-Type2923text / html
Content-Type666text/html; charset=utf-8
Content-Type6text/html;charset=UTF-8
Country_code33c_code=FI; Path=/; Secure
Edge-Cache-Tag3568docs.nvidia.com-brightspot-s3-prod
Edge-Cache-Tag2/nemo/index.html, /nemo
Edge-Cache-Tag2/nemo/retriever/index.html, /nemo/retriever, /nemo
Edge-Cache-Tag2/nemo-guardrails/index.html, /nemo-guardrails
Location3/%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20…0%20%20%20%20%20%20%20%20%20%20/
Location1/nemo/megatron-bridge/latest/parallelisms.html
Location1/nemo/retriever/latest/%20%20%20%20%20%20%20%20%20%20%20%20%20%20%2…20%20%20%20%20%20%20%20%20%20%20
Location1/nemo/megatron-bridge/latest/training/attention-optimizations.html
Location1/nemo-framework/user-guide/latest/overview.html
Location1/nemo/guardrails/latest/configure-rails/nemoguardrails/colang/v2_x/library/
Location1/nemo/megatron-bridge/latest/training/activation-recomputation.html
Location1/nemo/megatron-bridge/latest/training/mixed-precision.html
Location1/nemo/guardrails/
Location1/nemo/megatron-bridge/latest/training/cpu-offloading.html
Location1/nim/llama-3-1-nemotron-safety-guard-multilingual-8b-v1/latest/
Location1/nemo/guardrails/nemoguardrails/llm/prompts/
Location1/nemo/guardrails/nemoguardrails/colang/v2_x/library/
Location1/nemo/guardrails/latest/configure-rails/examples/v2_x/tutorial/hello_world_1/
Location1/nim/llama-3-1-nemotron-safety-guard-8b/latest/
Location1/nemo/megatron-bridge/latest/training/communication-overlap.html
Location1/nemo/
Location1/nemo/guardrails/latest/configure-rails/nemoguardrails/llm/prompts/
Location1/nemo/guardrails/examples/v2_x/tutorial/hello_world_1/
Pragma3595no-cache
Server3568AmazonS3
Server21AkamaiGHost
Server6istio-envoy
Strict-Transport-Security6max-age=31536000; includeSubDomains
Vary412Accept-Encoding
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X-Nv-Aws-Origin3568CloudFront
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No rows found, please edit your search term.

HTTP Caching by content type (only from crawlable domains)

Content typeCache typeURLs 🔽AVG lifetimeMIN lifetimeMAX lifetime
HTMLCache-Control + ETag + Last-Modified35680 s 0 s 0 s
RedirectCache-Control210 s 0 s 0 s
HTMLCache-Control60 s 0 s 0 s

HTTP Caching by domain

DomainCache typeURLs 🔽AVG lifetimeMIN lifetimeMAX lifetime
docs.nvidia.comCache-Control + ETag + Last-Modified35680 s 0 s 0 s
docs.nvidia.comCache-Control270 s 0 s 0 s

HTTP Caching by domain and content type

DomainContent typeCache typeURLs 🔽AVG lifetimeMIN lifetimeMAX lifetime
docs.nvidia.comHTMLCache-Control + ETag + Last-Modified35680 s 0 s 0 s
docs.nvidia.comRedirectCache-Control210 s 0 s 0 s
docs.nvidia.comHTMLCache-Control60 s 0 s 0 s

DNS info

Found 16 row(s).
DNS resolving tree
docs.nvidia.com
  docs.nvidia.com.edgekey.net
    e33907.a.akamaiedge.net
      IPv4: docs.nvidia.com.edgekey.net.
      IPv4: e33907.a.akamaiedge.net.
      IPv4: 80.239.150.75
      IPv4: 80.239.150.72
      IPv4: 80.239.150.91
      IPv4: 80.239.150.8
      IPv4: 80.239.150.59
      IPv4: 80.239.150.80
      IPv4: 80.239.150.35
      IPv4: 80.239.150.17
      IPv4: 80.239.150.96
DNS server: 127.0.0.53
No rows found, please edit your search term.

SSL/TLS info

InfoText
IssuerC = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
SubjectC = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
Valid fromJan 23 00:00:00 2026 GMT (VALID already 60.6 day(s))
Valid toJan 22 23:59:59 2027 GMT (VALID still for 304.4 day(s))
Supported protocolsTLSv1.2, TLSv1.3
RAW certificate outputCertificate:
    Data:
        Version: 3 (0x2)
        Serial Number:
            05:8b:c0:05:98:1f:e1:17:cc:79:11:99:b7:16:4c:b3
        Signature Algorithm: ecdsa-with-SHA384
        Issuer: C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
        Validity
            Not Before: Jan 23 00:00:00 2026 GMT
            Not After : Jan 22 23:59:59 2027 GMT
        Subject: C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
        Subject Public Key Info:
            Public Key Algorithm: id-ecPublicKey
                Public-Key: (256 bit)
                pub:
                    04:e0:0f:ef:1c:ad:88:20:f4:6d:01:82:74:00:4f:
                    0a:ef:8d:e6:ba:f7:b8:4b:d5:d9:02:cb:d6:dd:c8:
                    ab:1c:29:46:bd:61:a2:9a:5b:72:ea:5a:83:ed:a2:
                    c6:1a:32:3b:81:4f:6a:d4:dd:49:44:7a:24:79:d3:
                    d6:e0:f6:89:19
                ASN1 OID: prime256v1
                NIST CURVE: P-256
        X509v3 extensions:
            X509v3 Authority Key Identifier: 
                8A:23:EB:9E:6B:D7:F9:37:5D:F9:6D:21:39:76:9A:A1:67:DE:10:A8
            X509v3 Subject Key Identifier: 
                7A:CF:6E:B2:B2:A8:24:EC:B5:35:32:39:BA:B6:6F:3C:39:AD:DF:BF
            X509v3 Subject Alternative Name: 
                DNS:it.nvidia.com, DNS:*.admin.marketplace.nvidia.com, DNS:*.developer.nvidia.com, DNS:*.download.nvidia.com, DNS:*.geforce.com, DNS:*.gf-ahl.nvidia.com, DNS:*.gfe.nvidia.com, DNS:*.gfwsl.geforce.com, DNS:*.gsync.nvidia.com, DNS:*.ideas.nvidia.com, DNS:*.issacsim.nvidia.com, DNS:*.marketplace.nvidia.com, DNS:*.mellanox.com, DNS:*.nv-ahl.nvidia.com, DNS:*.nvidia.cn, DNS:*.nvidia.com, DNS:*.nvidia.partners, DNS:*.nvw.nvidia.com, DNS:*.order.store.nvidia.com, DNS:*.pforce.nvidia.com, DNS:*.stage.nvidia.com, DNS:*.store.nvidia.com, DNS:*.urm.nvidia.com, DNS:*.urmstg.nvidia.com, DNS:api-dev.nova.nvidia.com, DNS:api-prod.nova.nvidia.com, DNS:api-stage.nova.nvidia.com, DNS:api.docs.nvidia.com, DNS:archive.docs.nvidia.com, DNS:biosmod.partners.nvidia.com, DNS:biosmod.vendors.nvidia.com, DNS:blog.nvidia.com.br, DNS:blogs.nvidia.co.jp, DNS:blogs.nvidia.co.kr, DNS:blogs.nvidia.com.br, DNS:blogs.nvidia.com.tw, DNS:blogs.nvidia.fr, DNS:developer.qa.nvidia.cn, DNS:firmwaresign.partners.nvidia.com, DNS:gfwsl.stagegeforce.geforce.com, DNS:gx-target-rconfig-frontend-api-cdn.gx-stg.nvidia.com, DNS:gx-target-rconfig-frontend-api.gx-stg.nvidia.com, DNS:hdprogressive.3dvisionlive.com, DNS:hub.partners.nvidia.com, DNS:la.blogs.nvidia.com, DNS:layers.nvcr.io, DNS:layers.stg.nvcr.io, DNS:nvplm.stg.nvidia.com, DNS:ops.gx.nvidia.com, DNS:partners.legacy.nvidia.com, DNS:partners.nvbugs.nvidia.com, DNS:services-cdn.gfestage.nvidia.com, DNS:shield.nvidia.asia, DNS:shield.nvidia.co.jp, DNS:shield.nvidia.co.kr, DNS:shield.nvidia.hk, DNS:shield.nvidia.in, DNS:shield.nvidia.jp, DNS:stagepartners.legacy.nvidia.com, DNS:stagepartners.nvbugs.nvidia.com, DNS:stg.nvbugspro.nvidia.com, DNS:support-shield.nvidia.be, DNS:support-shield.nvidia.co.kr, DNS:support-shield.nvidia.co.uk, DNS:support-shield.nvidia.cz, DNS:support-shield.nvidia.de, DNS:support-shield.nvidia.dk, DNS:support-shield.nvidia.es, DNS:support-shield.nvidia.fi, DNS:support-shield.nvidia.fr, DNS:support-shield.nvidia.it, DNS:support-shield.nvidia.nl, DNS:support-shield.nvidia.no, DNS:support-shield.nvidia.pl, DNS:support-shield.nvidia.se, DNS:us.vrzn.download.nvidia.com, DNS:www.developer.nvidia.com, DNS:www.frameswingames.com, DNS:www.nvidia.com.ua, DNS:www.openacc.org, DNS:www.pgicompilers.com, DNS:www.pgroup.com
            X509v3 Certificate Policies: 
                Policy: 2.23.140.1.2.2
                  CPS: http://www.digicert.com/CPS
            X509v3 Key Usage: critical
                Digital Signature, Key Agreement
            X509v3 Extended Key Usage: 
                TLS Web Server Authentication
            X509v3 CRL Distribution Points: 
                Full Name:
                  URI:http://crl3.digicert.com/DigiCertGlobalG3TLSECCSHA3842020CA1-2.crl
                Full Name:
                  URI:http://crl4.digicert.com/DigiCertGlobalG3TLSECCSHA3842020CA1-2.crl
            Authority Information Access: 
                OCSP - URI:http://ocsp.digicert.com
                CA Issuers - URI:http://cacerts.digicert.com/DigiCertGlobalG3TLSECCSHA3842020CA1-2.crt
            X509v3 Basic Constraints: critical
                CA:FALSE
            CT Precertificate SCTs: 
                Signed Certificate Timestamp:
                    Version   : v1 (0x0)
                    Log ID    : 4C:63:DC:98:E5:9C:1D:AB:88:F6:1E:8A:3D:DE:AE:8F:
                                AB:44:A3:37:7B:5F:9B:94:C3:FB:A1:9C:FC:C1:BE:26
                    Timestamp : Jan 23 04:37:43.888 2026 GMT
                    Extensions: none
                    Signature : ecdsa-with-SHA256
                                30:45:02:20:36:F2:20:68:E0:4D:4C:95:16:27:1B:CC:
                                12:11:F3:9C:91:D9:EB:A3:C9:39:CF:DF:00:86:A4:59:
                                B8:DD:39:A8:02:21:00:9B:F2:24:86:F5:29:19:76:C3:
                                D7:1A:92:2F:B0:0B:75:6C:93:F6:D1:CA:53:72:19:57:
                                5B:70:CF:52:AA:5E:D8
                Signed Certificate Timestamp:
                    Version   : v1 (0x0)
                    Log ID    : 1C:9F:68:2C:E9:FA:F0:45:69:50:F8:1B:96:8A:87:DD:
                                DB:32:10:D8:4C:E6:C8:B2:E3:82:52:4A:C4:CF:59:9F
                    Timestamp : Jan 23 04:37:43.864 2026 GMT
                    Extensions: none
                    Signature : ecdsa-with-SHA256
                                30:46:02:21:00:FD:F8:B7:7E:12:7B:80:DF:9C:52:B6:
                                73:8E:FE:B9:98:69:CC:6F:D5:42:AD:84:21:65:85:FB:
                                B5:1E:87:1D:E8:02:21:00:B8:33:67:E9:9D:5D:28:04:
                                47:C1:7D:A7:76:20:4F:9D:C6:03:56:DE:63:C6:5C:88:
                                68:C3:BA:47:A4:2C:96:10
                Signed Certificate Timestamp:
                    Version   : v1 (0x0)
                    Log ID    : 60:4C:9A:AF:7A:7F:77:5F:01:D4:06:FC:92:0D:C8:99:
                                EB:0B:1C:7D:F8:C9:52:1B:FA:FA:17:77:3B:97:8B:C9
                    Timestamp : Jan 23 04:37:44.113 2026 GMT
                    Extensions: none
                    Signature : ecdsa-with-SHA256
                                30:45:02:21:00:95:1A:02:ED:FA:2E:32:B8:A1:A0:A4:
                                00:C3:C8:95:A6:44:24:A3:47:E1:36:83:E5:84:AE:CD:
                                CB:3B:64:FB:D4:02:20:1C:38:F5:89:01:D1:FA:2C:44:
                                5F:C7:7A:CB:AC:49:08:4C:AD:F0:4B:27:35:88:EC:B2:
                                CA:03:36:D7:44:85:68
    Signature Algorithm: ecdsa-with-SHA384
    Signature Value:
        30:66:02:31:00:87:16:b9:fc:bd:d2:cb:c4:35:45:80:9b:b7:
        fb:0c:17:89:67:5e:76:73:ca:bf:75:ab:3c:69:12:cb:77:89:
        0a:a2:21:31:3f:c6:64:53:eb:ce:d0:86:aa:05:cc:b3:31:02:
        31:00:d2:ad:f4:7f:f6:32:18:54:55:eb:a5:83:04:21:e5:c5:
        be:04:d0:91:bd:c6:87:fa:ca:4d:2c:c3:d5:6c:86:34:47:de:
        7c:1e:af:1e:2f:a5:80:bc:c6:da:aa:76:49:1b
RAW protocols output
=== ssl2 ===
s_client: Unknown option: -ssl2
s_client: Use -help for summary.

=== ssl3 ===
s_client: Unknown option: -ssl3
s_client: Use -help for summary.

=== tls1 ===
40973F837D730000:error:0A0000BF:SSL routines:tls_setup_handshake:no protocols available:../ssl/statem/statem_lib.c:104:
CONNECTED(00000003)
---
no peer certificate available
---
No client certificate CA names sent
---
SSL handshake has read 0 bytes and written 7 bytes
Verification: OK
---
New, (NONE), Cipher is (NONE)
Secure Renegotiation IS NOT supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
Early data was not sent
Verify return code: 0 (ok)
---

=== tls1_1 ===
40E718CECA740000:error:0A0000BF:SSL routines:tls_setup_handshake:no protocols available:../ssl/statem/statem_lib.c:104:
CONNECTED(00000003)
---
no peer certificate available
---
No client certificate CA names sent
---
SSL handshake has read 0 bytes and written 7 bytes
Verification: OK
---
New, (NONE), Cipher is (NONE)
Secure Renegotiation IS NOT supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
Early data was not sent
Verify return code: 0 (ok)
---

=== tls1_2 ===
depth=2 C = US, O = DigiCert Inc, OU = www.digicert.com, CN = DigiCert Global Root G3
verify return:1
depth=1 C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
verify return:1
depth=0 C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
verify return:1
CONNECTED(00000003)
---
Certificate chain
 0 s:C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
   i:C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
   a:PKEY: id-ecPublicKey, 256 (bit); sigalg: ecdsa-with-SHA384
   v:NotBefore: Jan 23 00:00:00 2026 GMT; NotAfter: Jan 22 23:59:59 2027 GMT
 1 s:C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
   i:C = US, O = DigiCert Inc, OU = www.digicert.com, CN = DigiCert Global Root G3
   a:PKEY: id-ecPublicKey, 384 (bit); sigalg: ecdsa-with-SHA384
   v:NotBefore: Apr 14 00:00:00 2021 GMT; NotAfter: Apr 13 23:59:59 2031 GMT
---
Server certificate
-----BEGIN CERTIFICATE-----
MIINATCCDIagAwIBAgIQBYvABZgf4RfMeRGZtxZMszAKBggqhkjOPQQDAzBZMQsw
CQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMTMwMQYDVQQDEypEaWdp
Q2VydCBHbG9iYWwgRzMgVExTIEVDQyBTSEEzODQgMjAyMCBDQTEwHhcNMjYwMTIz
MDAwMDAwWhcNMjcwMTIyMjM1OTU5WjBtMQswCQYDVQQGEwJVUzETMBEGA1UECBMK
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AgEGCCqGSM49AwEHA0IABOAP7xytiCD0bQGCdABPCu+N5rr3uEvV2QLL1t3Iqxwp
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dmlkaWEuY29tghMqLnVybXN0Zy5udmlkaWEuY29tghdhcGktZGV2Lm5vdmEubnZp
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CisGAQQB1nkCBAIEggFvBIIBawFpAHYATGPcmOWcHauI9h6KPd6uj6tEozd7X5uU
w/uhnPzBviYAAAGb6STVUAAABAMARzBFAiA28iBo4E1MlRYnG8wSEfOckdnro8k5
z98AhqRZuN05qAIhAJvyJIb1KRl2w9caki+wC3Vsk/bRylNyGVdbcM9Sql7YAHcA
HJ9oLOn68EVpUPgbloqH3dsyENhM5siy44JSSsTPWZ8AAAGb6STVOAAABAMASDBG
AiEA/fi3fhJ7gN+cUrZzjv65mGnMb9VCrYQhZYX7tR6HHegCIQC4M2fpnV0oBEfB
fad2IE+dxgNW3mPGXIhow7pHpCyWEAB2AGBMmq96f3dfAdQG/JINyJnrCxx9+MlS
G/r6F3c7l4vJAAABm+kk1jEAAAQDAEcwRQIhAJUaAu36LjK4oaCkAMPIlaZEJKNH
4TaD5YSuzcs7ZPvUAiAcOPWJAdH6LERfx3rLrEkITK3wSyc1iOyyygM210SFaDAK
BggqhkjOPQQDAwNpADBmAjEAhxa5/L3Sy8Q1RYCbt/sMF4lnXnZzyr91qzxpEst3
iQqiITE/xmRT687QhqoFzLMxAjEA0q30f/YyGFRV66WDBCHlxb4E0JG9xof6yk0s
w9VshjRH3nwerx4vpYC8xtqqdkkb
-----END CERTIFICATE-----
subject=C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
issuer=C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
---
No client certificate CA names sent
Peer signing digest: SHA256
Peer signature type: ECDSA
Server Temp Key: ECDH, prime256v1, 256 bits
---
SSL handshake has read 4749 bytes and written 338 bytes
Verification: OK
---
New, TLSv1.2, Cipher is ECDHE-ECDSA-AES256-GCM-SHA384
Server public key is 256 bit
Secure Renegotiation IS supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
SSL-Session:
    Protocol  : TLSv1.2
    Cipher    : ECDHE-ECDSA-AES256-GCM-SHA384
    Session-ID: 474CCCF5910C0D548AC0F779EEC064C4EB2A9BCA1539F4B3E9DBE44113AB1457
    Session-ID-ctx: 
    Master-Key: 3C5A74E229F785066B5D04928D8DBF414F918219C9D4279D6D74E2EB695472D30813F95E0A0B02198B755668D5AEA436
    PSK identity: None
    PSK identity hint: None
    SRP username: None
    TLS session ticket lifetime hint: 83100 (seconds)
    TLS session ticket:
    0000 - 00 00 84 73 5f 33 94 4a-93 cb a8 5c 8b e8 4f 73   ...s_3.J...\..Os
    0010 - aa 8f 52 49 46 37 ef 52-1f 7d 91 74 ae d4 97 ea   ..RIF7.R.}.t....
    0020 - a7 8d b5 8f e7 fa 3f 1c-be a4 48 31 cd 12 ca a4   ......?...H1....
    0030 - 7b cb c7 7e 5a dc e5 c8-e8 71 23 c5 15 d4 05 c5   {..~Z....q#.....
    0040 - fd 1f b3 e5 5a 0e e6 0b-df 9c 30 47 5b 23 be fc   ....Z.....0G[#..
    0050 - 62 e0 75 99 b1 9a 28 64-8f 06 e4 03 04 c8 79 2d   b.u...(d......y-
    0060 - ac b6 65 ef 09 fd 4b 23-6b 17 b4 da 53 52 90 2e   ..e...K#k...SR..
    0070 - 68 43 a6 d5 66 a8 0d 83-53 43 f7 96 3a 34 85 1d   hC..f...SC..:4..
    0080 - 35 bd e1 d6 61 bb 84 1b-4d f8 9b 70 47 ae fc 91   5...a...M..pG...
    0090 - 5d e1 b8 1b 87 4c fb a4-3c 94 48 43 c8 77 ff 13   ]....L..<.HC.w..
    00a0 - e0 32 ae 57 c9 b0 63 91-33 93 fe c1 dd af fd 14   .2.W..c.3.......
    00b0 - 03 a5 b7 d1 95 ba b9 96-7e b9 e0 10 f2 1f ad 67   ........~......g
    00c0 - 39 95 17 c0 13 a2 a7 62-1a c1 ff 22 51 3c 2d 75   9......b..."Q<-u

    Start Time: 1774361420
    Timeout   : 7200 (sec)
    Verify return code: 0 (ok)
    Extended master secret: no
---
DONE

=== tls1_3 ===
depth=2 C = US, O = DigiCert Inc, OU = www.digicert.com, CN = DigiCert Global Root G3
verify return:1
depth=1 C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
verify return:1
depth=0 C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
verify return:1
CONNECTED(00000003)
---
Certificate chain
 0 s:C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
   i:C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
   a:PKEY: id-ecPublicKey, 256 (bit); sigalg: ecdsa-with-SHA384
   v:NotBefore: Jan 23 00:00:00 2026 GMT; NotAfter: Jan 22 23:59:59 2027 GMT
 1 s:C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
   i:C = US, O = DigiCert Inc, OU = www.digicert.com, CN = DigiCert Global Root G3
   a:PKEY: id-ecPublicKey, 384 (bit); sigalg: ecdsa-with-SHA384
   v:NotBefore: Apr 14 00:00:00 2021 GMT; NotAfter: Apr 13 23:59:59 2031 GMT
---
Server certificate
-----BEGIN CERTIFICATE-----
MIINATCCDIagAwIBAgIQBYvABZgf4RfMeRGZtxZMszAKBggqhkjOPQQDAzBZMQsw
CQYDVQQGEwJVUzEVMBMGA1UEChMMRGlnaUNlcnQgSW5jMTMwMQYDVQQDEypEaWdp
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w9VshjRH3nwerx4vpYC8xtqqdkkb
-----END CERTIFICATE-----
subject=C = US, ST = California, L = Santa Clara, O = NVIDIA Corporation, CN = it.nvidia.com
issuer=C = US, O = DigiCert Inc, CN = DigiCert Global G3 TLS ECC SHA384 2020 CA1
---
No client certificate CA names sent
Peer signing digest: SHA256
Peer signature type: ECDSA
Server Temp Key: X25519, 253 bits
---
SSL handshake has read 4615 bytes and written 329 bytes
Verification: OK
---
New, TLSv1.3, Cipher is TLS_AES_256_GCM_SHA384
Server public key is 256 bit
Secure Renegotiation IS NOT supported
Compression: NONE
Expansion: NONE
No ALPN negotiated
Early data was not sent
Verify return code: 0 (ok)
---
DONE

Crawler stats

Basic stats
Total execution time466 s
Total URLs3595
Total size349 MB
Requests - total time1883 s
Requests - avg time524 ms
Requests - min time20 ms
Requests - max time2.9 s
Requests by status200: 3565
301: 21
404: 9

Analysis stats

Found 21 row(s).
Class::methodExec time 🔽Exec count
AccessibilityAnalyzer::checkMissingAriaLabels18 s 3565
AccessibilityAnalyzer::checkMissingLabels15 s 3565
AccessibilityAnalyzer::checkMissingRoles13 s 3565
BestPracticeAnalyzer::checkHeadingStructure12 s 3574
AccessibilityAnalyzer::checkMissingLang11 s 3565
BestPracticeAnalyzer::checkMaxDOMDepth10 s 3574
BestPracticeAnalyzer::checkNonClickablePhoneNumbers4.6 s 3574
BestPracticeAnalyzer::checkMissingQuotesOnAttributes1 s 3574
SslTlsAnalyzer::getTLSandSSLCertificateInfo547 ms 1
SeoAndOpenGraphAnalyzer::analyzeHeadings470 ms 1
SecurityAnalyzer::checkHtmlSecurity467 ms 3573
AccessibilityAnalyzer::checkImageAltAttributes448 ms 3565
BestPracticeAnalyzer::checkInlineSvg401 ms 3574
SecurityAnalyzer::checkHeaders82 ms 3573
SeoAndOpenGraphAnalyzer::analyzeSeo10 ms 1
SeoAndOpenGraphAnalyzer::analyzeOpenGraph7 ms 1
BestPracticeAnalyzer::checkTitleUniqueness0 ms 1
BestPracticeAnalyzer::checkMetaDescriptionUniqueness0 ms 1
BestPracticeAnalyzer::checkBrotliSupport0 ms 1
BestPracticeAnalyzer::checkWebpSupport0 ms 1
BestPracticeAnalyzer::checkAvifSupport0 ms 1
No rows found, please edit your search term.

Content processor stats

Found 12 row(s).
Class::methodExec time 🔽Exec count
HtmlProcessor::findUrls10 s 3595
NextJsProcessor::applyContentChangesBeforeUrlParsing682 ms 3574
JavaScriptProcessor::findUrls628 ms 3574
CssProcessor::findUrls73 ms 3574
AstroProcessor::findUrls50 ms 3574
AstroProcessor::applyContentChangesBeforeUrlParsing3 ms 3574
NextJsProcessor::findUrls1 ms 3574
JavaScriptProcessor::applyContentChangesBeforeUrlParsing1 ms 3574
SvelteProcessor::applyContentChangesBeforeUrlParsing0 ms 3574
SvelteProcessor::findUrls0 ms 3574
HtmlProcessor::applyContentChangesBeforeUrlParsing0 ms 3595
CssProcessor::applyContentChangesBeforeUrlParsing0 ms 3574
No rows found, please edit your search term.

Crawler info

Version 2.1.0.20260317
Executed At 2026-03-24 14:02:43
Command siteone-crawler --url=https://docs.nvidia.com/nemo --markdown-export-dir=/tmp/siteone-nvidia_canary --markdown-exclude-selector=header,footer,nav,.sidebar,.menu,.breadcrumb,script,style --timeout=30 --workers=5 --disable-javascript --disable-styles --disable-fonts --disable-images --disable-files --no-color --hide-progress-bar --output=text --include-regex=/nemo/ --max-depth=4
Hostname ubuntu-8gb-hel1-1
User-Agent Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/26.0.0.0 Safari/537.36 siteone-crawler/2.1.0.20260317