NVIDIA-NeMo / Automodel

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Die Installation von pypi:nemo-automodel@0.5.0 zieht 131 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.

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        "Standard ML": 19356,
        "Jupyter Notebook": 38342
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      "pushed_at": "2026-07-25T06:36:04Z",
      "created_at": "2025-05-21T21:45:47Z",
      "owner_type": "Organization",
      "updated_at": "2026-07-25T06:36:08Z",
      "description": "🚀 Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support",
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          "oid": "3ebd99a5e65c11ddfa73f964260bbb774827b104",
          "body": "* fix(distributed): support packed CP for Llama and Qwen2\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(ci): declare node count for packed CP recipes\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* feat(models): add packed CP support for dense Qwen3\n\nS\n[…]\n\n* test(distributed): gate packed TP CP test by GPU count\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix(distributed): support packed CP for Llama, Qwen2, and Qwen3 (#2999)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-25T06:36:02Z",
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          "oid": "d8c354b0662e0cc489d715e586e6e3c69fe2ab33",
          "body": "… (#3192)\n\napply_submodule_checkpointing() wraps the attention submodule by searching\nattr names (\"self_attn\", \"attention\", \"attn\"), but hybrid linear-attention\nmodels (Qwen3-Next, Qwen3.5, Qwen3.5-MoE) name their Gated DeltaNet mixer\n\"linear_attn\". Those layers were therefore never checkpoint-wrapp\n[…]\nred-by: Amol Khanna <amol.khanna@crowdstrike.com>\nCo-authored-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "fix(distributed): activation-checkpoint Qwen3-Next linear_attn layers…",
          "author_name": "amolkhanna",
          "author_login": "amolkhanna",
          "committed_at": "2026-07-25T05:01:02Z",
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          "oid": "bd592f8829d9fafddd95abc5fea9af9934e087e8",
          "body": "Signed-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix(glm): size GLM5.2 release CI jobs (#3210)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-25T00:20:30Z",
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          "oid": "35b1fcab72515236525bbeb57225cc825d1615ae",
          "body": "* fix(ci): shard Nemotron Super vLLM deploy across 8 GPUs\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* test(vllm): enable expert parallel for large MoE deploys\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* ci: bump deploy dockerfile to 26.04\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@\n[…]\nyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-authored-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(ci): shard Nemotron Super vLLM deploy across 8 GPUs (#3061)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-24T23:00:34Z",
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          "oid": "622cc24ba9206eee9cde6067ca0a50d95dcc8b25",
          "body": "…(#3207)\n\nGLM-5.2 uses noaux_tc MoE load balancing: the FP32 e_score_correction_bias\nmust be updated from per-expert token counts after each optimizer step, but\nneither GlmMoeDsaModel nor GlmMoeDsaForCausalLM exposed update_moe_gate_bias,\nso the recipe-side hasattr hook never fired and the bias was \n[…]\nlayers, FakeBalancedGate, and\ngate_bias_update_factor=0 overrides); the outer CausalLM delegates.\n\nSigned-off-by: larkzhang-nv <larkz@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "feat(glm_moe_dsa): expose update_moe_gate_bias on GLM MoE DSA models …",
          "author_name": "jQizhang",
          "author_login": "jQizhang",
          "committed_at": "2026-07-24T18:34:32Z",
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          "body": "Signed-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix(vlm): size qwen3.6 medpix CI configs (#3209)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-24T18:33:04Z",
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        },
        {
          "oid": "dfd1401a65f1e73887dcbaa4328f0a6312b1ecb1",
          "body": "…ting (#3133)\n\n* fix(dist): keep profiler record-function ops out of SAC replay accounting\n\ntorch 2.13's FSDP2 runs its pre/post-forward hooks under\ntorch.autograd.profiler.record_function, which emits dispatchable\ntorch.ops.profiler ops. When an FSDP module boundary sits inside a\nselective-activati\n[…]\ngned-off-by: HuiyingLi <willwin.lee@gmail.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(dist): keep profiler record-function ops out of SAC replay accoun…",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-24T17:45:39Z",
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          "oid": "fc57de71faefcef21c558853e4618328c197f5f6",
          "body": "…ath (#3122)\n\n* refactor(diffusion): migrate recipe onto typed RecipeConfig build() path\n\nAligns the diffusion training recipe with the LLM/VLM recipes: every YAML\nsection is coerced once at the recipe boundary into a typed config that owns\nconstruction via build(...), and the recipe body becomes th\n[…]\nSigned-off-by: Pranav Prashant Thombre <pthombre@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "refactor(diffusion): migrate recipe onto typed RecipeConfig build() p…",
          "author_name": "Pranav Thombre",
          "author_login": "pthombre",
          "committed_at": "2026-07-24T17:40:26Z",
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          "oid": "380423c63c55f9b97cf7246504d900bb3325e287",
          "body": "… (#3161)\n\n* feat(dllm): add DiffusionGemma generation via the built-in HF sampler\n\nDiffusionGemma ships its own diffusion sampler in transformers >= 5.11\n(entropy-bounded denoising with adaptive stopping; the pinned 5.12.1\nincludes generation_diffusion_gemma.py), so generation follows the model\nrat\n[…]\nards on top.\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat(dllm): add DiffusionGemma generation via the built-in HF sampler…",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-24T16:10:19Z",
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        {
          "oid": "4027eb1a4972e002254bf0b00d14cf13d9b90db5",
          "body": "* perf(kernels): add QuACK backend\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(packaging): sync PyTorch image lock for QuACK\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* test(perf): allow QuACK kernel warmup\n\nSigned-off-by: Alexandros Koumparoulis\n[…]\n: NeMo Bot <nemo-bot@nvidia.com>\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>\nCo-authored-by: NeMo Bot <nemo-bot@nvidia.com>\nCo-authored-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "feat(kernels): add QuACK backend (#3115)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-24T14:38:05Z",
          "body_truncated": true,
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        },
        {
          "oid": "d41256417b61d56f1c6dd39983de2cb36e2f4df1",
          "body": "…n (#3193)\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "feat(checkpoint): preserve intrinsic fp32 during offline consolidatio…",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-24T14:27:19Z",
          "body_truncated": false,
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        },
        {
          "oid": "104878f558471d21f6a7ea8e5c5abbcf59966576",
          "body": "* build(deps): pin megatron-fsdp to 0.5.0\n\nMove the megatron-fsdp requirement from the permissive >=0.2.3 range to\nan exact 0.5.0 pin and refresh both uv lock files accordingly. Later\nreleases changed the fully_shard precision API and DTensor handling, so\nthe supported version must be explicit for t\n[…]\nBy: Claude Opus 4.8 <noreply@anthropic.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(distributed): Megatron-FSDP 0.5.0 compatibility (#2986)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-24T14:17:03Z",
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          "is_coding_agent": true
        },
        {
          "oid": "bb9a62c892863c7250460e1ce564cfc9f66136fc",
          "body": "…on (#2987)\n\n* feat(distributed): shape TPLinear/LinearLoRA graphs for async-TP fusion\n\nInductor's async tensor-parallel pass (_micro_pipeline_tp, enabled via\nenable_async_tensor_parallel) fuses collectives with matmuls by\npattern-matching the reshape-mm-reshape graph that F.linear emits for\n3-D inp\n[…]\nributed): move TP linear helpers to shared\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "feat(distributed): shape TPLinear/LinearLoRA graphs for async-TP fusi…",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-24T14:09:17Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "190a2b7145b2d64ba4461bf13dc2aec3b754b549",
          "body": "* fix: prefer Automodel config registry lookup\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* docs: require config registry review checks\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix: annotate custom config resolver\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix: prefer Automodel config registry lookup (#3202)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-24T13:09:04Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "983bac3c44bddc8847986220a4c687de74eb10a8",
          "body": "* fix(glm): apply LoRA to TileLang MLA KV projection\n\nSigned-off-by: Shahaf Wagner <shahafwg@gmail.com>\n\n* feat(glm): add GLM-5.2 LoRA finetune recipe (TileLang MLA)\n\nAdds examples/llm_finetune/glm/glm_5.2_lora.yaml, a 16-node (128-GPU, cp=1/ep=128) LoRA fine-tuning config for GLM-5.2 on the TileLan\n[…]\nludes the required ci: section (recipe_owner/nodes/time) for release CI auto-discovery.\n\nSigned-off-by: Shahaf Wagner <shahafwg@gmail.com>\n\n---------\n\nSigned-off-by: Shahaf Wagner <shahafwg@gmail.com>",
          "is_bot": false,
          "headline": "fix(glm): apply LoRA to TileLang MLA KV projection (#3176)",
          "author_name": "Shahaf Wagner",
          "author_login": "shahafwa",
          "committed_at": "2026-07-24T11:57:12Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "4cc72911e5f82f3e2014fe0f352725e6369b8c90",
          "body": "* docs(retrieval): complete fine-tuning guide integration\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>\n\n* fix(retrieval): align the public dataset config\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>\n\n* docs(retrieval): ali\n[…]\n <oholworthy@users.noreply.github.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Oliver Holworthy <oholworthy@users.noreply.github.com>\nCo-authored-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "docs(retrieval): complete fine-tuning guide integration (#2306)",
          "author_name": "Oliver Holworthy",
          "author_login": "oliverholworthy",
          "committed_at": "2026-07-24T01:13:42Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "b0b53b0f6251ed968b6a970c69a3439728b3c1b3",
          "body": "Fused bf16 SDPA is gradient-unstable for Gemma4 on Hopper (grad_norm NaN ~step 22,\nthen loss NaN, with attn_implementation=sdpa and local_batch_size>=2). Run SDPA\nwith fp32 q/k/v and install it as the sdpa attention when Gemma4 uses sdpa.\n\nSigned-off-by: Amineh Dadsetan <amineh.dadsetan@gmail.com>",
          "is_bot": false,
          "headline": "fix(gemma4): run SDPA in fp32 to avoid #2208 NaN on Hopper (#3141)",
          "author_name": "Amineh Dadsetan",
          "author_login": "aminehd",
          "committed_at": "2026-07-23T18:46:12Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "fd18270430fc82d1a84b0fb5ccea7b457c55f7ee",
          "body": "* feat(dllm): LoRA recipes for llada/llada2/nemotron and adapter generation\n\n- New LoRA example recipes mirroring their SFT configs plus a peft block:\n  llada_lora.yaml (covers both LLaDA attention/MLP layouts; unmatched\n  patterns are no-ops), llada2_lora.yaml (16B MoE: attention + dense-layer\n  ML\n[…]\n state_dict.\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat(dllm): add lora to dllm  (#3163)",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-23T18:08:03Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "bee559ddb2f54e8a9dc40e064e4d86e1c687ef15",
          "body": "* fix(ci): preserve HF meta init for device-mapped loads\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* ci: increase Qwen3 MoE parity timeout\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(ci): preserve HF meta init for device-mapped loads (#3188)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-23T18:05:14Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "601dbafaed8aa925210df39a6d67169df5ae3fea",
          "body": "fix(ci): run coverage after successful CI summary\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "fix(ci): AUT-964 restore Codecov after skipped GB200 jobs (#3205)",
          "author_name": "svcnemo-autobot",
          "author_login": "svcnemo-autobot",
          "committed_at": "2026-07-23T18:01:21Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "66c5a8bbd98ef6500dbd477b410bf5c14387c329",
          "body": "* feat: Support preemption checkpointing\n\nSigned-off-by: edjson <edisonggacc@gmail.com>\n\n* fixed typos\n\nSigned-off-by: edjson <edisonggacc@gmail.com>\n\n* fix: background srun, and added docs\n\nSigned-off-by: edjson <edisonggacc@gmail.com>\n\n* Apply docs corrections from code review\n\nCo-authored-by: jge\n[…]\nroulis <153118171+akoumpa@users.noreply.github.com>\nCo-authored-by: Abhishree Thittenamane <47577437+athitten@users.noreply.github.com>\nCo-authored-by: jgerh <163925524+jgerh@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat: Support preemption checkpointing (#3007)",
          "author_name": "Edison",
          "author_login": "edjson",
          "committed_at": "2026-07-23T17:20:48Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "d761ae2cce1c3af97ad14894e9df27c142d53657",
          "body": "…3189)\n\n* enable image+text training for vision retrieval\n\n* simplify injecting text with image logic",
          "is_bot": false,
          "headline": "feat: enable text inclusion alongside images in retrieval training (#…",
          "author_name": "rnyak",
          "author_login": "rnyak",
          "committed_at": "2026-07-23T16:50:58Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "c179031a74171981a0b57bcfb8af276c87259b06",
          "body": "* fix: honor memory-efficient LoRA toggle for fused MLPs\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix: disable memory-efficient LoRA in throughput recipes\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix: keep memory-efficient LoRA for Qwen3.5 benchmark\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix(peft): honor memory-efficient LoRA opt-out (#3126)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-23T15:40:01Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "f78e01e754ce8cbb2dc171ec37fd1a72f11452fc",
          "body": "…er (#3144)",
          "is_bot": false,
          "headline": "fix(datasets): keep system turns in the sharegpt conversation convert…",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-23T14:03:04Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "025bb132e032a089c5ff580049bc2dcdc521b9f4",
          "body": null,
          "is_bot": false,
          "headline": "feat: add checkpoint staging wait option (#3131)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-23T14:01:44Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "995e8d64cdc6b5134266e7a6cb3b81f107c519c3",
          "body": "* ci: restore single L0 GPU unit-test job\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* test(ci): trim slow CPU L0 coverage\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* ci: reduce L0 GPU tests to two shards\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "ci: reduce L0 GPU tests to two shards (#3201)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-23T12:32:23Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "5983424df87ba99271b074727f468f0eeb964554",
          "body": "Signed-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "docs(fern): add legacy URL redirects (#3203)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-23T10:34:12Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "70cb0869206c2c4b68547b0cb814687237de016e",
          "body": "… (#2937)\n\n* refactor(distributed): introduce CPSharder, retire private CP batch keys\n\nModels that own their CP batch sharding now return a CPSharder dataclass\n(under the 'cp_sharder' batch key) from prepare_model_inputs_for_cp,\nreplacing the private batch-key side channel (_cp_make_batch_fn,\n_cp_me\n[…]\n\n\nDeferred: the cp_sharder.py contiguous-shard function docstrings are long but get\nmerged/rewritten by the follow-up shard_batch_contiguous collapse, so they are\ncompressed there rather than churned…",
          "is_bot": false,
          "headline": "refactor(distributed): unify CP input prep and dispatch across models…",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-23T09:28:40Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "8918b8cd1dc0ecbbb1309878d3f9b8bb9e238dee",
          "body": "* test(deepseek-v4): add random-init pretraining CI\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(ci): select H100 for DeepSeek V4 pretrain\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(ci): use synthetic data for DeepSeek V4 pretrain\n\nSigned-off\n[…]\nvidia.com>\n\n* test(ci): add DeepSeek V4 pretrain pipeline\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "test(ci): add DeepSeek V4 Flash pretrain coverage (#3128)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-23T07:52:24Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "81e7f01f431c31a60d607b9245f1337d8dcf9e1b",
          "body": "…rt (#3199)\n\nPR #2929 added flash_attention_3 and flash_attention_4 to the set of\nflash-attention variants configure_packing patches, so flash_attention_3 is\nno longer an unsupported (no-op) backend. test_noop_for_unsupported_backends\nstill parametrized it as unsupported and asserted the FA2 shim wa\n[…]\ne\nno-op test, and parametrize test_patches_flash_attention_utils over all three\nflash-attention variants so the newly supported fa3/fa4 paths have coverage.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "test(packing): fix stale unsupported-backend test after fa3/fa4 suppo…",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-23T06:27:43Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "40392130e350902e3aaf4b31eb7bfdec92ada596",
          "body": "Signed-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(checkpoint): add DCP CPU offload option (#3130)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-23T02:04:11Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "59d82e3a9421493a490c873569960b1a8de2ae31",
          "body": "* feat(attention): support flash_attention_3 and flash_attention_4\n\ntransformers >= 5.x dispatches attn_implementation=flash_attention_3 (dist\nflash-attn-3, module flash_attn_interface) and flash_attention_4 (dist\nflash-attn-4, module flash_attn.cute) natively. This change makes those\nselectable end\n[…]\n\n---------\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat(attention): support flash_attention_3 and flash_attention_4 (#2929)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-22T22:39:56Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "92eb9fc8f489b361e9d3bffad556f64a8d8530ad",
          "body": "…(#3151)\n\n* feat(examples): add CoderForge SFT data pipeline for CP validation\n\nPhase 1 of AM-492 (AM-555). Adds examples/convergence/coderforge/:\n\n- prefilter_dataset.py: load togethercomputer/CoderForge-Preview, parse and\n  clean the OpenHands trajectories (JSON-string messages/tools + union-schem\n[…]\n@gmail.com>\nSigned-off-by: athitten <abhishreetm@gmail.com>\nCo-authored-by: Claude Opus 4.8 <noreply@anthropic.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat(examples): Gemma4-31B CoderForge data pipeline + CP SFT recipes …",
          "author_name": "Abhishree Thittenamane",
          "author_login": "athitten",
          "committed_at": "2026-07-22T21:45:09Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "5e292306f0b4c4e34daf26fe8d86b432d2aacabd",
          "body": "* fix(distributed): preserve canonical activation checkpoint keys\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* ci: extend Nemotron single-GPU timeout\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* ci: right-size Nemotron single-GPU timeout\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(distributed): preserve canonical activation checkpoint keys (#3152)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-22T20:56:42Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "53ef40b1f608d6fa1aebb4cbd67b997666b3129a",
          "body": "* feat(distributed): add block-diagonal varlen context parallelism for packed sequences\n\nAdd a self-contained CP implementation for packed (multi-document)\nsequences where masking must stay block-causal per document, which the\nload-balanced DTensor context_parallel path cannot express:\n\n- batch: con\n[…]\ntributed): harden packed block-diagonal CP\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "feat(distributed): block-diagonal varlen CP for packed sequences (#2989)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-22T18:04:44Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "79378e6261f28df02a17533e8430c230e1002e55",
          "body": "Signed-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(checkpoint): restore adapters through DDP wrappers (#3150)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-22T15:08:07Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "df7dcc6a372e98e99e21554f9e25e9160cb75e48",
          "body": "* fix(kd): use torch adam fp32 masters\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(kd): resolve storage dtype from raw config\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(kd): scope fp32 storage fallback to KD recipes\n\nSigned-off-by: Alexandro\n[…]\nfix(kd): use recipe config accessors for dtype resolution\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix(kd): use fp32 master weight copy (#3019)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-22T13:31:59Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "829d6621849852713c7116d256a329d211765634",
          "body": "* fix(checkpoint): add bounded retention window\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>\n\n* fix(checkpoint): log retention policy at startup\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>\n\n* fix(checkpoint): harden reten\n[…]\n final review cleanup\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>\n\n---------\n\nSigned-off-by: Oliver Holworthy <1216955+oliverholworthy@users.noreply.github.com>",
          "is_bot": false,
          "headline": "fix(checkpoint): add bounded retention window (#2416)",
          "author_name": "Oliver Holworthy",
          "author_login": "oliverholworthy",
          "committed_at": "2026-07-22T09:22:19Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "7cbae6878cf2cc55c69c416955dc66089429a912",
          "body": "…#3136)\n\n* fix: make grad norm robust to finite overflow\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix: repair near-zero input embedding rows\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* test: cover distributed embedding row repair\n\nSigned-off-by: A\n[…]\nli@nvidia.com>\n\n* fix: handle empty local gradient shards\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix: prevent damaged token embeddings from dominating grad clipping (…",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-22T08:39:27Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "c59eba6c514074f55b3718fd566403572284782e",
          "body": "* feat(models): add Laguna model implementation\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* test(models): keep Laguna smoke test on dense path\n\nKeep the causal-LM smoke test focused on Laguna wiring while the separate\nunit test continues to validate the sparse MoE layer construction and\nrou\n[…]\noreply@anthropic.com>\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n---------\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "feat(models): add Laguna model implementation (#3148)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-22T01:34:01Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "c37f04cde41dd91e2018622cc31e07d0c1462710",
          "body": "* feat(dllm): add LLaDA2 generation support\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* refactor(dllm): keep LLaDA2 options sampler-local\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* docs(dllm): address LLaDA2 inference review\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* docs(dllm): apply technical publications review\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>",
          "is_bot": false,
          "headline": "feat(dllm): add LLaDA2 generation support (#3092)",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-21T18:17:58Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "b1b083e789a324c9697b8217093aeb92ca49cb08",
          "body": "ci: gate GB200 tests and container build on DISABLE_GB200_TESTS\n\nEnable GB200 CI by default, but skip the cicd-e2e-tests-gb200 jobs and the\nGCP (GB200) container build in the build matrix when the repo variable\nDISABLE_GB200_TESTS is 'true'. The Nemo_CICD_Test summary excludes gb200_\njobs from the failure count in that case, so a disabled run stays green.\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "ci: AUT-895 gate GB200 tests on DISABLE_GB200_TESTS variable (#3118)",
          "author_name": "svcnemo-autobot",
          "author_login": "svcnemo-autobot",
          "committed_at": "2026-07-21T17:36:11Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "52e061ccebc80829bf3712c131f8ba5f5198796a",
          "body": "* Add Laguna SFT recipe and docs\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* docs: add Laguna README entry\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* docs: use Laguna S 2.1 model id\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* docs: link Laguna README entry to HF\n\nSigned-o\n[…]\nipe\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* docs: add Laguna recipe CI owner\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n---------\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "docs: add Laguna SFT docs and recipe (#3146)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-21T17:27:37Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "01d9ab0460bc299cdc5f87dd3ba9dfec03d38b3e",
          "body": null,
          "is_bot": false,
          "headline": "fix(moe): preserve HSDP replica gradient synchronization (#3135)",
          "author_name": "wangzhxg",
          "author_login": "wangzhxg",
          "committed_at": "2026-07-21T09:03:44Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "2e40c6222a35efe72ed1446b655a516e0cf9b882",
          "body": "* feat(bagel): make TE and fused projections configurable\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* fix(bagel): harden TE and fused projections\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* fix(bagel): support fused distributed checkpoint init\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n[…]\nned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* perf(bagel): enable TE in example recipes by default\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>",
          "is_bot": false,
          "headline": "feat(bagel): add TE support (#2895)",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-21T03:28:00Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "66c72a99c6a21bda5ea50dc56d7d1410528b19ef",
          "body": "* fix(ci): preserve retrieval evaluation schedule\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* fix(ci): preserve retrieval release schedule\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(ci): preserve retrieval evaluation schedule (#3139)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-20T21:59:38Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "ce862ce43613ade8881bd071fe71a369a8a8436e",
          "body": "* build(deps): bump base container to 26.06-cuda13.3\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>\n\n* ci(install-test): keep cuda-dl-base on 26.04-cuda13.2\n\nSigned-off-by: Dong Hyuk Chang <9426164+tho\n[…]\n-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>\nCo-authored-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "test(vlm): add checkpoint robustness coverage (#3112)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-20T21:28:05Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "c659a21e74988b84634d31afbf6325be10bd55ee",
          "body": "Signed-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(checkpoint): isolate consolidation timeout from NCCL (#3108)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-20T20:17:59Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "9005cc155e4ef26d50746346b48b318f4b03c502",
          "body": "* ci: shard GPU unit tests into 5 pytest-shard chunks\n\nSplit the single L0_Unit_Tests_GPU job into five parallel matrix shards\nusing pytest-shard, plumbing --shard-id/--num-shards through the\ntest-template action and tests/run_test.sh.\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>\n\n* \n[…]\nia.com>\n\n* chore(deps): regenerate uv-pytorch.lock for pytest-shard\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>\n\n---------\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "ci: AUT-911 shard GPU unit tests into 5 pytest-shard chunks (#3138)",
          "author_name": "svcnemo-autobot",
          "author_login": "svcnemo-autobot",
          "committed_at": "2026-07-20T18:03:11Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "106bc6aacc0e65c9cfe40317b55eb9b27ba8a8d3",
          "body": "…own (#3134)\n\nfix(transformers): keep custom MiniMaxM3VL config when transformers ships its own\n\ntransformers 5.12 (bumped in 14d17731) added a native minimax_m3_vl model\ntype with the same model_type string and class names as our custom\nimplementation. _register_custom_configs skips registration wh\n[…]\nitten against the native config and runs green, so\nits behavior is left unchanged.\n\nRegression test pins CONFIG_MAPPING['minimax_m3_vl'] to our class.\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix(transformers): keep custom M3 config when transformers ships its …",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-20T15:47:12Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "3cd3ed2a119fbf0ea23b347d7a881be16c159af0",
          "body": "* build(deps): bump base container to 26.06-cuda13.3\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>\n\n* ci(install-test): keep cuda-dl-base on 26.04-cuda13.2\n\nSigned-off-by: Dong Hyuk Chang <9426164+tho\n[…]\n <yuhez@nvidia.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>\nCo-authored-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\nCo-authored-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "build(deps): bump base container to 26.06-cuda13.3 (#2983)",
          "author_name": "Dong Hyuk Chang",
          "author_login": "thomasdhc",
          "committed_at": "2026-07-20T14:01:18Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "0c41f71363d940a4830ad0b142c8c6b204e67648",
          "body": "* fix(checkpoint): gather PEFT adapter across PP stages so full LoRA is saved\n\nSigned-off-by: hyfine <835083304@qq.com>\n\n* fix(checkpoint): only warn on PP gather collapse when >1 rank has adapters\n\nAddresses review feedback: the degenerate-gather guard warned whenever\nmerged_n <= max(per_rank), whi\n[…]\n one non-empty rank.\n\nSigned-off-by: hyfine <835083304@qq.com>\n\n---------\n\nSigned-off-by: hyfine <835083304@qq.com>\nCo-authored-by: Alexandros Koumparoulis <153118171+akoumpa@users.noreply.github.com>",
          "is_bot": false,
          "headline": "fix(checkpoint): gather PEFT adapter across PP stages (#3096)",
          "author_name": "Muqing",
          "author_login": "hyfine",
          "committed_at": "2026-07-20T11:51:41Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "cdaaff9139d4b3a2aaa5b1ef03226c932f6110b2",
          "body": "Add Inkling README news\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "docs: Add Inkling README news (#3129)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-19T08:51:44Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "ba4ec358fecfec3bc3524a3e8a56677a2815878b",
          "body": "* feat(vlm): THD packed-sequence support for Qwen3-VL-MoE (collater, recipe, capability, tests)\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n* fix(vlm): guard THD packing to cp_size=1; document mRoPE/CP scope\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n* fix(vlm): use self.mesh_context.cp_size in T\n[…]\nen3-VL-30B-A3B with TE\nattention and packing_format=thd on MedPix: 20 healthy steps, loss 1.98->1.63.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(vlm): add THD packed-sequence support for Qwen3-VL-MoE (#3052)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-18T14:22:48Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "e54ea84b4dc68793be900ede9c29cf98a995dcf5",
          "body": "… (#2783)\n\n* ci(dllm): add dLLM SFT nightly train-to-generate launcher and recipes\n\nAdd a dLLM SFT nightly CI test folder:\n- tests/ci_tests/scripts/dllm_sft_launcher.sh: train->generate smoke. torchrun\n  finetune via examples/dllm_sft/finetune.py (selects recipe class from the\n  config 'recipe:' fie\n[…]\niffusionGemma to nightly SFT\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\nCo-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "ci(dllm): add dLLM SFT nightly train-to-generate launcher and recipes…",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-18T08:25:51Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "a5b9283045094a1ab5cbcd19c60cdd536ea1e20a",
          "body": "* feat(models): add Inkling VLM MoE support\n\nSigned-off-by: hemildesai <hemild@nvidia.com>\n\n* Update uv lock\n\nSigned-off-by: NeMo Bot <nemo-bot@nvidia.com>\n\n* refactor(pp): reuse centralized process group warmup\n\nSigned-off-by: hemildesai <hemild@nvidia.com>\n\n* refactor(pp): use default NCCL communi\n[…]\nmild@nvidia.com>\nSigned-off-by: NeMo Bot <nemo-bot@nvidia.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: NeMo Bot <nemo-bot@nvidia.com>\nCo-authored-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "feat(models): add Inkling VLM MoE support (#3095)",
          "author_name": "Hemil Desai",
          "author_login": "hemildesai",
          "committed_at": "2026-07-18T03:45:43Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "5008ea66c33583bb3fe2f782fbffd56da4135933",
          "body": "… (#3113)\n\n* fix(vlm): resolve get_rope_index from the base model for packed mRoPE\n\nTransformers defines get_rope_index on the base model, not on the\n*ForConditionalGeneration that model_parts holds, and DDP or MegatronFSDP add\nanother wrapper on top without proxying attribute reads. The recipe's pl\n[…]\nt of setup(). Fall back to the\nattribute lookups alone when the object does not carry named_children.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "fix(vlm): resolve get_rope_index from the base model for packed mRoPE…",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-18T03:04:58Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "eb0470922bc01557fa424aea09a06b64d3578573",
          "body": "* ci: add HF hub cache preflight check\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>\n\n* refactor(ci): use exit code for hf_cache_check decision\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@users\n[…]\nus 4.6 (1M context) <noreply@anthropic.com>\n\n---------\n\nSigned-off-by: Dong Hyuk Chang <9426164+thomasdhc@users.noreply.github.com>\nCo-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "ci: add HF hub cache preflight check (#3119)",
          "author_name": "Dong Hyuk Chang",
          "author_login": "thomasdhc",
          "committed_at": "2026-07-17T20:43:47Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "a0d025e4ad50152960f4516dabb190a8cfcc3720",
          "body": "* fix(ci): restore Ministral3 checkpoint robustness\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* fix(ci): make Ministral3 recipes blocking\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(ci): restore Ministral3 checkpoint robustness (#3111)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-17T18:48:53Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "4827dbbaadef007fce81584e1c544d36994de641",
          "body": "* feat(loss): add chunked fp32 path to MaskedCrossEntropy via chunk_size\n\nComputing masked cross-entropy on the last pipeline stage upcasts the full\n[N, V] logits to fp32 and additionally saves cross_entropy's fp32 log-softmax\nfor backward, which dominates the loss-side memory peak for large-vocabul\n[…]\nls): harden FA2 packing compatibility shim\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix: bound chunked CE memory and preserve packing masks (#2996)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-17T18:37:22Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "f02d3607ae35ef570f89ac7f7c3b54dc54918ab2",
          "body": "* feat(training): add opt-in setup-time prewarms for cuBLAS, fla autotune, and NCCL groups\n\ncuBLAS/cuBLASLt workspaces, Triton autotune caches (flash-linear-attention\ngated-delta-net backward kernels), and NCCL communicators all initialize\nlazily on first use. When that first use lands in step 1 at \n[…]\nmaining technical publications suggestions\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "feat(training): add opt-in setup-time prewarms (#2992)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-17T18:36:53Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "5adfd2206a5e4cc2432b692a6bf2f2a40cd13d80",
          "body": "…(#2884)\n\n* test(ci): remove deprecated 26.10 models from nightly and release CI\n\nDrop deprecated families from nightly recipe lists, exempt them from\nrelease auto-discovery, update benchmark overrides, and remove stale\ngolden convergence values.\n\n* fix(ci): keep Llama 3.2-1B and retrieval tests whi\n[…]\ncontinue to run in CI while the remaining deprecated\nfamilies (Baichuan, Qwen2.5/Seed, Mistral/Mixtral, GLM 4.5/4-9B, Kimi-VL,\nGemma 2/3, Phi, Granite, OLMo, Falcon 3, StarCoder, Cohere) stay removed.",
          "is_bot": false,
          "headline": "test(ci): remove deprecated 26.10 models from nightly and release CI …",
          "author_name": "Abhishree Thittenamane",
          "author_login": "athitten",
          "committed_at": "2026-07-17T16:41:58Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "8a83fdcee3c5025df0f64399cf771236dfb0242d",
          "body": "…s (#2995)\n\n* feat(moe): safe fail-closed tensor parallelism for custom MoE models\n\nEnable tensor parallelism on the non-expert token path of custom MoE\nmodels instead of asserting tp_size == 1, with fail-closed validation:\n\n- Resolve TP plans only from an explicit tp_shard_plan or a registered\n  ar\n[…]\nfactor: move tied-weight helpers to shared\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(moe): safe TP and EP/TP gradient correctness for custom MoE model…",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-17T14:20:26Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "4364e4bd22ebbe3b64614840933a248581b2d708",
          "body": "* feat(kd): support separate student and teacher meshes\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* docs(kd): add separate-mesh example configs\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* docs(kd): add VLM separate-mesh examples\n\nSigned-off-by: Alexa\n[…]\nidia.com>\n\n* test(kd): cover separate mesh recipe helpers\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "feat(kd): support separate student and teacher meshes (#2954)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-17T07:56:55Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "af88b008065ef77547a58377498d637271ea69b9",
          "body": "Signed-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(test): use eager attention for Nemotron-H HF loads (#3100)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-16T19:44:49Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "9fd184099087884b0908dfd150c7f453bc436d23",
          "body": "Codecov upload for pull requests from forks landed in a pending state\nbecause the PR number could not be inferred: the fork CI runs on a\nrefs/heads/pull-request/<n> branch, so codecov/codecov-action has no PR\ncontext. Pass override_pr and override_commit from the get-pr-info step\n(mirroring the existing base_sha wiring) so the coverage report is\nassociated with the correct PR and head commit.\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "fix(ci): pass PR number and commit to Codecov for fork PRs (#3101)",
          "author_name": "svcnemo-autobot",
          "author_login": "svcnemo-autobot",
          "committed_at": "2026-07-16T18:31:43Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "e522eda71804bef99680e8e43baf898d66425116",
          "body": "Signed-off-by: Zeyu Zhou <zezhou@nvidia.com>",
          "is_bot": false,
          "headline": "fix(bagel): enable periodic garbage collection (#3105)",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-16T17:08:56Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "c40259786db0f36548b6efb7c4bdef60008dc0f6",
          "body": "…ataloader (#2390)\n\n* wip\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* fix(datasets): satisfy import-linter independence contract\n\nDataloaderConfig.build (the config-driven replacement for the recipe's\nbuild_dataloader) crossed the \"Components must not import each other\"\ncont\n[…]\n-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\nCo-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "refactor(datasets): typed Config + build per dataset, config-driven d…",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-16T16:21:55Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "2dca34ea99e2ccb48e4c33225050cd74a4922b1d",
          "body": "* feat(speculative): add DFlash validation metrics\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n* fix(speculative): skip disabled W&B metrics\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(speculative): add DFlash validation metrics (#3072)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-16T15:11:56Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "59eca013119f9e485bf13f15bc007b8157edc13a",
          "body": "…998)\n\n* refactor(models): add TieSupport enum and single tie_word_embeddings guard\n\nReplace reject_unsupported_tied/untied_word_embeddings with a single\nreject_unsupported_tie_word_embeddings(model_cls, config) driven by a per-class\nTieSupport declaration. Migrate the 30 existing guard call sites 1\n[…]\nuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Achyuthan Sivasankar <achyuthan.sivasankar@gmail.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "refactor(models): single tie_word_embeddings guard via TieSupport (#2…",
          "author_name": "achyuthan.s",
          "author_login": "Achyuthan-S",
          "committed_at": "2026-07-16T14:52:43Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "90ae61715923dfacd22f0ea9fc679c8c764ceb2f",
          "body": "Signed-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "test: clean up KD test process group (#3090)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-16T14:44:35Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "10ee7c19f2855d6fe35f2a04daf218762d76c206",
          "body": "Revert \"chore(skills): add Regent Open Plugin manifest (#3097)\"\n\nThis reverts commit af4da2e0620d1e718fc7538374bf8551404b70fe.\n\nSigned-off-by: oliver könig <okoenig@nvidia.com>",
          "is_bot": false,
          "headline": "chore(skills): remove Open Plugin manifest (superseded) (#3099)",
          "author_name": "oliver könig",
          "author_login": "ko3n1g",
          "committed_at": "2026-07-16T09:43:34Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "af4da2e0620d1e718fc7538374bf8551404b70fe",
          "body": "Expose this repo's skills/ as a skills-only Regent Open Plugin so in-cluster\nCI agents (implement-author + base analyst) can activate them as $automodel:<skill>.\nAdds only .plugin/plugin.json; Regent scans ./skills/ by default. No behavior\nchange for humans or Claude Code (which reads .claude/skills).\n\nSigned-off-by: oliver könig <okoenig@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "chore(skills): add Regent Open Plugin manifest (#3097)",
          "author_name": "oliver könig",
          "author_login": "ko3n1g",
          "committed_at": "2026-07-16T08:24:38Z",
          "body_truncated": false,
          "is_coding_agent": true
        },
        {
          "oid": "29322e1e15ae705a8221a36cacbdf0b3ccff9571",
          "body": "… (#3083)\n\nfix(speculative): keep DSpark target_layer_ids within [0, N-2] for SGLang servability\n\nThe standard SGLang runtime captures aux/context features via\nset_eagle3_layers_to_capture (effectively capturing the input of layer id+1), so\nit cannot produce a feature for -1 (the embedding, no captu\n[…]\nm is unchanged.\n\nvalidate_target_layer_ids now warns (not errors) when -1 or N-1 is present, since\nthose ids remain valid for AutoModel's own spec_generate.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "fix(speculative): keep DSpark target_layer_ids in [0, N-2] for SGLang…",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-16T02:59:41Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "49676eed612296f27c1d723495914c7fc4c3d805",
          "body": "…(#3081)\n\n* test(speculative): add EAGLE-3 fp8 draft convergence smoke for SM89+\n\nAdds a turnkey harness to validate fp8 draft-training convergence on\nfp8-capable hardware (H100/Ada, sm_89+), the last open fp8 item in the\nspeculative-decoding tracking issue (#2958). The fp8 feature (#2963)\nshipped w\n[…]\n: khazic <khazzz1c@gmail.com>\n\n* chore: re-trigger CI (gb200 coverage step flaked on missing uuidgen)\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "test(speculative): add EAGLE-3 fp8 draft convergence smoke for SM89+ …",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-16T02:57:27Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "6e5d52b5bd6136ab8e3f126dc815c17577051e14",
          "body": "Signed-off-by: yaoyu-33 <yaoyu.094@gmail.com>",
          "is_bot": false,
          "headline": "fix(perf): use GPT-OSS head dimension in FLOPs accounting (#3091)",
          "author_name": "Yu Yao",
          "author_login": "yaoyu-33",
          "committed_at": "2026-07-15T23:48:41Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "bc9ce776f3eda61f79e4c2ec80c8b8fd12a42ebb",
          "body": "* feat(retrieval): add Ministral3 embedding distillation recipe\n\nAdd EmbeddingDistillRecipe with RetrieverStudentWithProjection /\nRetrieverTeacherEmbeddingEncoder, distillation losses (cosine / MSE /\nInfoNCE-distill), intermediate-layer distillation, cross-tokenizer\ncached-teacher support, bi-encode\n[…]\nll.yaml\n\n* Update test_infonce.py\n\n* Update test_retrieval_distill_recipe.py\n\n---------\n\nSigned-off-by: Vinay Raman <viraman@nvidia.com>\nCo-authored-by: rnyak <16246900+rnyak@users.noreply.github.com>",
          "is_bot": false,
          "headline": "feat: add Ministral3 embedding distillation recipe (#3058)",
          "author_name": "vinay-raman",
          "author_login": "vinay-raman",
          "committed_at": "2026-07-15T21:40:55Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "0a0433ded1cc35d3471948b6daca99b20f4ab44c",
          "body": "chore(ci): bump claude review template to v1.8.4\n\nUpdate the FW-CI-templates _claude_review.yml pin from the v1.8.3 commit\n(7d857ec) to the equivalent v1.8.4 commit (209ac79), keeping the inline\nversion comment in sync.\n\nSigned-off-by: svcnemo-autobot <svcnemo-autobot@nvidia.com>",
          "is_bot": false,
          "headline": "chore(ci): AUT-852 bump claude review template to v1.8.4 (#3087)",
          "author_name": "svcnemo-autobot",
          "author_login": "svcnemo-autobot",
          "committed_at": "2026-07-15T15:37:03Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "2b768ada9ca1c3a0ecf23271d326765320afe09f",
          "body": "* feat(speculative): add Gemma4 EAGLE-3 target support\n\nRegister Gemma4 (`Gemma4ForConditionalGeneration`) as an EAGLE-3 target so\n`train_eagle3.py` can train a draft against Gemma4 checkpoints (E2B/E4B/31B\ndense and 26B-A4B MoE).\n\nThe draft is Llama-style dense (it consumes only post-block hidden s\n[…]\nexpert MoE backbone is hooked and supervised\nidentically to a dense target; no code change is needed.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(speculative): add Gemma4-26B-A4B MoE EAGLE-3 example config (#3079)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-15T14:38:50Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "ce24f7afc4b44a22426d92d8239aa0b8f20e2610",
          "body": "* feat(speculative): add Gemma4 EAGLE-3 target support\n\nRegister Gemma4 (`Gemma4ForConditionalGeneration`) as an EAGLE-3 target so\n`train_eagle3.py` can train a draft against Gemma4 checkpoints (E2B/E4B/31B\ndense and 26B-A4B MoE).\n\nThe draft is Llama-style dense (it consumes only post-block hidden s\n[…]\n8 GiB bf16) plus the draft fits on a single 80 GB\nGPU with freeze_embeddings and expandable_segments.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(speculative): add Gemma4-31B EAGLE-3 example config (#3077)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-15T14:05:36Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "79bfece527396d1c77397f72890dc9b42905ff78",
          "body": "* fix(test): use SDPA for Nemotron-H HF reload\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n* fix(test): avoid timeout during rank-zero HF reload\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>",
          "is_bot": false,
          "headline": "fix(test): use SDPA for Nemotron-H HF reload (#3060)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-15T14:03:27Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "9a6fee931ada2ab2f501d5af458f1342a51ba84b",
          "body": "* feat(speculative): add Gemma4 EAGLE-3 target support\n\nRegister Gemma4 (`Gemma4ForConditionalGeneration`) as an EAGLE-3 target so\n`train_eagle3.py` can train a draft against Gemma4 checkpoints (E2B/E4B/31B\ndense and 26B-A4B MoE).\n\nThe draft is Llama-style dense (it consumes only post-block hidden s\n[…]\n recipe as the E2B config; only the\ntarget path and output dirs change (E4B: 2560 hidden, 42 layers).\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(speculative): add Gemma4-E4B EAGLE-3 example config (#3073)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-15T13:58:45Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "e8e45a1d76e947c6e6534dcb93879bef6b3d1388",
          "body": "* fix(dllm): remove obsolete DiffusionGemma HF compatibility\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n* docs(dllm): address DiffusionGemma review feedback\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>\n\n---------\n\nSigned-off-by: Zeyu Zhou <zezhou@nvidia.com>",
          "is_bot": false,
          "headline": "fix(dllm): remove obsolete DiffusionGemma HF compatibility (#3067)",
          "author_name": "Zeyu Zhou",
          "author_login": "zyzhou5",
          "committed_at": "2026-07-15T13:45:37Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "c144e4b7a9e2772c82e24e1592462295dc6d6667",
          "body": "Register Gemma4 (`Gemma4ForConditionalGeneration`) as an EAGLE-3 target so\n`train_eagle3.py` can train a draft against Gemma4 checkpoints (E2B/E4B/31B\ndense and 26B-A4B MoE).\n\nThe draft is Llama-style dense (it consumes only post-block hidden states from\nthe frozen target's text backbone) with two G\n[…]\ner locates the decoder under\n`model.language_model.layers`, and `num_hidden_layers` is read from `text_config`.\n\nAdds a unit test and an E2B example config.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(speculative): add Gemma4 EAGLE-3 target support (#3071)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-15T09:57:21Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "395e3de6c93bafcd7cefac808c99edfbb0caf2a2",
          "body": "* Fix Kimi K2 config loading without remote code\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* fix: move Kimi K2 config under Kimi package\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n---------\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix: Kimi K2 config loading without remote code (#3065)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-15T02:31:13Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "55a3bfbe7a2b5ecb566e5a5b2d944ff2b496c259",
          "body": "Signed-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix(ci): use HybridEP for Step 3.5 benchmark (#3069)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-15T00:16:54Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "4e809d0de1a9f2036e0e51822109936ffcc9f6e0",
          "body": "…t (#2357)\n\n* refactor(vlm-recipe): replace _target_ whitelist with marker-attribute opt-in\n\nbuild_model in recipes/vlm/finetune.py used to enumerate every accepted\nmodel _target_ inline -- the NeMoAutoModelFor* classmethods plus a\ngemma4-specific helper (_is_gemma4_joint_target) that did a lazy imp\n[…]\n\n(present via a fake module, absent via a forced ImportError) plus the\n_is_recipe_target None short-circuit, independent of installed deps.\n\n---------\n\nSigned-off-by: Abhishree <abhishreetm@gmail.com>",
          "is_bot": false,
          "headline": "refactor(vlm): gate build_model via recipe-side model-target allowlis…",
          "author_name": "Abhishree Thittenamane",
          "author_login": "athitten",
          "committed_at": "2026-07-14T16:06:51Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "80ba6a018a0c84517855c6125560fabe02c04c82",
          "body": "* fix(cp): preserve gradients when sharding VLM inputs\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* test(cp): cover padded gradients and HSDP ranks\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n* test(cp): stress scaling with 200 padding rows\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>\n\n---------\n\nSigned-off-by: HuiyingLi <willwin.lee@gmail.com>",
          "is_bot": false,
          "headline": "fix(cp): preserve gradients when sharding VLM inputs (#2931)",
          "author_name": "Huiying",
          "author_login": "HuiyingLi",
          "committed_at": "2026-07-14T13:41:22Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "7c7237e5f12adb2c9363b68bfcc0526c068047ec",
          "body": "* feat(optim): support per-parameter-group learning rate\n\nAdd `param_group_overrides` to the optimizer config so a subset of\nparameters, matched by name, can be given its own optimizer parameter\ngroup with a learning-rate / weight-decay multiplier. This mirrors\nMegatron-LM's per-group `lr_mult` scal\n[…]\nusedAdam path needs a GPU, so it stays covered by the FSDP2 validation run\nrather than the CPU suite.\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(optim): support per-parameter-group learning rate (#3046)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-14T13:04:48Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "6c704d55ff9dd6204d1c7eab143a852c384e6987",
          "body": "* fix(distributed): checkpoint canonical child modules\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* proper fix\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* revert\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* rm\n\nSigned-off-by: A\n[…]\nnvidia.com>\n\n* fix(models): preserve wrapped fp32 buffers\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "fix(models): handle checkpoint-wrapped fp32 buffers (#3059)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-14T10:12:47Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "55ed9becc4b65aa8a3f0e287473b3148f449ab55",
          "body": "… (#3045)\n\n* feat(datasets): add optional parallel pre-tokenization before packing\n\nSequence packing first runs one full pass over the dataset, which for a\nlazily-tokenizing map-style dataset (e.g. ChatDataset) tokenizes every\nsample serially in a single process. On realistic multi-turn SFT data thi\n[…]\npply all review suggestions from jgerh on the text-dataset guide (wording, casing, table formatting).\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "feat(datasets): add optional parallel pre-tokenization before packing…",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-14T06:46:25Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "6c47ea6681d1e9dd1361a2eb91a53302b7304bfd",
          "body": "…ath (#2993)\n\n* fix(moe): checkpoint trainable vision towers on the expert-parallel path\n\nThe MoE parallelizer's apply_ac only iterates the text/MTP decoder stack,\nand the generic FSDP2/DDP activation-checkpointing scope handling does not\nrun for expert-parallel configs (ep_size > 1), so MoE VLMs wi\n[…]\n-By: Claude Fable 5 <noreply@anthropic.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(moe): checkpoint trainable vision towers on the expert-parallel p…",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-14T01:09:35Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "9af3b45a8fefd817e9ff562e8e8780d54e8cf68e",
          "body": "…(#2997)\n\n* fix(optim): drop zero-numel local DTensor shards before TE FusedAdam\n\nFSDP2 shards every parameter along dim-0 across the shard group; any\nparameter with dim-0 smaller than the group (e.g. the biases, norm\nweights, and class/position embeddings of a small dense vision tower\nsharded over \n[…]\n-By: Claude Fable 5 <noreply@anthropic.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(optim): drop zero-numel local DTensor shards before TE FusedAdam …",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-13T20:34:16Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "37ac2dcd565cc126fa6ed5035274d56527c2e3d0",
          "body": "… (#3001)\n\nThe Tulu-3 VLM SFT recipes pointed make_meta_dataset at a local\ntulu3_train_meta.json that requires a one-time data-prep dump. That file\nis absent in Nemo-CI, so the runs failed with FileNotFoundError.\n\nAdd make_tulu3_dataset, which pulls allenai/tulu-3-sft-mixture straight\nfrom the Hub a\n[…]\nJSON path uses (_convert_sharegpt_to_conversation), keeping the data\ncomposition identical (no turn cap, system turns dropped, rows in split\norder). Point the three tulu3 recipes at it.\n\nFixes AM-628.",
          "is_bot": false,
          "headline": "fix(vlm): load Tulu-3 directly from HF Hub instead of local meta JSON…",
          "author_name": "Abhishree Thittenamane",
          "author_login": "athitten",
          "committed_at": "2026-07-13T18:26:44Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "446b43338896f1dd31768978078cc108f59544a7",
          "body": "…by version (#3025)\n\n* fix(distributed): resolve transformers-v5 module paths in VLM AC layer-group specs\n\nTransformers v5 nests the Qwen2-VL/Qwen2.5-VL towers under the shared\n`model.` backbone and flattened the Llava/Gemma3 CLIP/SigLIP vision\ntowers, so the layer-group FQNs in _get_model_layer_gro\n[…]\n-By: Claude Fable 5 <noreply@anthropic.com>\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "fix(distributed): resolve VLM AC layer-group paths structurally, not …",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-13T17:09:09Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "d9e2557241f931407a14c95b660d811402aac8d8",
          "body": "* fix(transformers): gate _tie_weights_nemo on tie_word_embeddings flag\n\n_tie_weights_nemo re-tied lm_head.weight to the input embedding for any\nmodel exposing _nemo_tied_weights_keys, without consulting\nconfig.tie_word_embeddings. For untied models this aliased away the\ntrained lm_head loaded by fr\n[…]\nmers): align nano4 source parity threshold\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\n\n---------\n\nSigned-off-by: Yuhe Zhang <yuhez@nvidia.com>\nCo-authored-by: Claude Fable 5 <noreply@anthropic.com>",
          "is_bot": false,
          "headline": "test(transformers): add source-load parity coverage (#2960)",
          "author_name": "Yuhe Zhang",
          "author_login": "yuhezhang-ai",
          "committed_at": "2026-07-13T16:44:41Z",
          "body_truncated": true,
          "is_coding_agent": true
        },
        {
          "oid": "aaa158dc8e8f6f67a77a4f94da6a42bb0a66824e",
          "body": "Signed-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "fix(dspark): omit unmeasured positional acceptance rates (#3050)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-13T15:04:08Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "b968af6ecbee35dd22439c8a641b14d5c63b3073",
          "body": "* icnldue cutlass\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\n\n* Update uv lock\n\nSigned-off-by: NeMo Bot <nemo-bot@nvidia.com>\n\n---------\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>\nSigned-off-by: NeMo Bot <nemo-bot@nvidia.com>\nCo-authored-by: NeMo Bot <nemo-bot@nvidia.com>",
          "is_bot": false,
          "headline": "ci: include cutlass deps (#3056)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-13T14:50:17Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "5bf95de57386a8c58c13f82ba7ef42931ed506b9",
          "body": "* fix(recipe): add Qwen3 MoE THD chat template\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n* fix(recipe): add OLMo generation chat template\n\nSigned-off-by: khazic <khazzz1c@gmail.com>\n\n---------\n\nSigned-off-by: khazic <khazzz1c@gmail.com>",
          "is_bot": false,
          "headline": "fix(recipe): add generation-marked chat templates (#3051)",
          "author_name": "khazzz1c",
          "author_login": "khazic",
          "committed_at": "2026-07-13T14:32:52Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "d6e5787d718d2ab53d6e39f85206bef5f982a51c",
          "body": "add uv\n\nSigned-off-by: Alexandros Koumparoulis <akoumparouli@nvidia.com>",
          "is_bot": false,
          "headline": "docs: add uv run prefix (#3057)",
          "author_name": "Alexandros Koumparoulis",
          "author_login": "akoumpa",
          "committed_at": "2026-07-13T13:41:52Z",
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                  }
                ],
                "max_points": 54
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              {
                "key": "commit_distribution",
                "name": "Commit distribution",
                "detail": "top contributor authored 24% of commits",
                "points": 17.2,
                "status": "partial",
                "details": [
                  {
                    "code": "top_contributor_share",
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                      "share": 24
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                  }
                ],
                "max_points": 22.5
              },
              {
                "key": "contributor_breadth",
                "name": "Contributor breadth",
                "detail": "99 contributors",
                "points": 13.5,
                "status": "met",
                "details": [
                  {
                    "code": "contributors_sampled",
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                      "count": 99
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                ],
                "max_points": 13.5
              },
              {
                "key": "openssf_scorecard_contributors",
                "name": "OpenSSF Scorecard: Contributors",
                "detail": "project has 24 contributing companies or organizations",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
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            ]
          },
          {
            "key": "responsiveness",
            "band": "good",
            "name": "Issue & PR responsiveness",
            "note": null,
            "notes": [],
            "value": 79,
            "inputs": {
              "merged_prs": 2071,
              "open_issues": 151,
              "closed_issues": 361,
              "issue_closed_ratio": 0.705,
              "closed_unmerged_prs": 399
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            "components": [
              {
                "key": "issue_resolution",
                "name": "Issue resolution",
                "detail": "70% of issues closed",
                "points": 33,
                "status": "partial",
                "details": [
                  {
                    "code": "issues_closed_share",
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                      "share": 70
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                  }
                ],
                "max_points": 46.75
              },
              {
                "key": "pr_acceptance",
                "name": "PR acceptance",
                "detail": "2071/2470 decided PRs merged",
                "points": 32.1,
                "status": "partial",
                "details": [
                  {
                    "code": "decided_prs_merged",
                    "params": {
                      "merged": 2071,
                      "decided": 2470
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                  }
                ],
                "max_points": 38.25
              },
              {
                "key": "openssf_scorecard_code_review",
                "name": "OpenSSF Scorecard: Code-Review",
                "detail": "Found 27/30 approved changesets -- score normalized to 9",
                "points": 13.5,
                "status": "partial",
                "details": [],
                "max_points": 15
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            ]
          },
          {
            "key": "stewardship",
            "band": "moderate",
            "name": "Ownership & stewardship",
            "note": null,
            "notes": [],
            "value": 66,
            "inputs": {
              "followers": 1399,
              "owner_type": "Organization",
              "is_verified": null,
              "owner_login": "NVIDIA-NeMo",
              "public_repos": 27,
              "account_age_days": 423
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            "components": [
              {
                "key": "ownership_backing",
                "name": "Ownership backing",
                "detail": "organization-owned",
                "points": 30,
                "status": "met",
                "details": [
                  {
                    "code": "owner_organization",
                    "params": {}
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                ],
                "max_points": 30
              },
              {
                "key": "verified_domain",
                "name": "Verified domain",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "owner_reach",
                "name": "Owner reach",
                "detail": "1,399 followers of NVIDIA-NeMo",
                "points": 22.6,
                "status": "partial",
                "details": [
                  {
                    "code": "owner_followers",
                    "params": {
                      "count": 1399,
                      "login": "NVIDIA-NeMo"
                    }
                  }
                ],
                "max_points": 25
              },
              {
                "key": "track_record",
                "name": "Track record",
                "detail": "27 public repos, account ~1 yr old",
                "points": 12.9,
                "status": "partial",
                "details": [
                  {
                    "code": "public_repos",
                    "params": {
                      "count": 27
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                  },
                  {
                    "code": "account_age_years",
                    "params": {
                      "years": 1
                    }
                  }
                ],
                "max_points": 25
              }
            ]
          },
          {
            "key": "package_maintenance",
            "band": "excellent",
            "name": "Package maintenance",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "packages": [
                "nemo-automodel"
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              "ecosystems": "pypi",
              "any_deprecated": false,
              "min_days_since_publish": 22
            },
            "components": [
              {
                "key": "published_resolvable",
                "name": "Published & resolvable",
                "detail": "1 package(s) on pypi",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "packages_published",
                    "params": {
                      "count": 1,
                      "ecosystems": "pypi"
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                  }
                ],
                "max_points": 25
              },
              {
                "key": "publish_recency",
                "name": "Publish recency",
                "detail": "latest publish 22 days ago",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "publish_recency",
                    "params": {
                      "days": 22
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                  }
                ],
                "max_points": 35
              },
              {
                "key": "version_history",
                "name": "Version history",
                "detail": "7 published versions",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "published_versions",
                    "params": {
                      "count": 7
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                  }
                ],
                "max_points": 20
              },
              {
                "key": "not_deprecated",
                "name": "Not deprecated",
                "detail": "active, not deprecated or yanked",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "package_not_deprecated",
                    "params": {}
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                ],
                "max_points": 20
              }
            ]
          }
        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
      },
      {
        "key": "engineering",
        "band": "excellent",
        "name": "Engineering Quality",
        "value": 96,
        "weight": 0.2,
        "metrics": [
          {
            "key": "engineering_practices",
            "band": "excellent",
            "name": "Engineering practices",
            "note": null,
            "notes": [],
            "value": 94,
            "inputs": {
              "has_ci": true,
              "has_tests": true,
              "has_editorconfig": false,
              "has_linter_config": true,
              "has_precommit_config": true
            },
            "components": [
              {
                "key": "ci_workflows",
                "name": "CI workflows",
                "detail": "22 workflow(s)",
                "points": 24,
                "status": "met",
                "details": [
                  {
                    "code": "ci_workflows",
                    "params": {
                      "count": 22
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                  }
                ],
                "max_points": 24
              },
              {
                "key": "tests_present",
                "name": "Tests present",
                "detail": null,
                "points": 24,
                "status": "met",
                "details": [],
                "max_points": 24
              },
              {
                "key": "linter_config",
                "name": "Linter config",
                "detail": ".flake8, .pylintrc",
                "points": 16,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
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                  }
                ],
                "max_points": 16
              },
              {
                "key": "pre_commit_hooks",
                "name": "Pre-commit hooks",
                "detail": null,
                "points": 9.6,
                "status": "met",
                "details": [],
                "max_points": 9.6
              },
              {
                "key": "editorconfig",
                "name": ".editorconfig",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 6.4
              },
              {
                "key": "openssf_scorecard_ci_tests",
                "name": "OpenSSF Scorecard: CI-Tests",
                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
                "points": 20,
                "status": "met",
                "details": [],
                "max_points": 20
              }
            ]
          },
          {
            "key": "documentation",
            "band": "excellent",
            "name": "Documentation",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "topics": [
                "llm",
                "vlm",
                "finetuning",
                "gemma3",
                "llama",
                "llama3",
                "mistral",
                "openai",
                "qwen3",
                "gpt-oss",
                "qwen3-next",
                "glm",
                "kimi-k2",
                "deepseek-v3-2",
                "minimax-m2",
                "gemma4",
                "qwen3-6",
                "deepseek-v4",
                "agent"
              ],
              "has_wiki": true,
              "homepage": "https://docs.nvidia.com/nemo/automodel/nightly/index.html",
              "has_readme": true,
              "has_docs_dir": true,
              "has_description": true
            },
            "components": [
              {
                "key": "readme",
                "name": "README",
                "detail": null,
                "points": 30,
                "status": "met",
                "details": [],
                "max_points": 30
              },
              {
                "key": "documentation_directory",
                "name": "Documentation directory",
                "detail": null,
                "points": 25,
                "status": "met",
                "details": [],
                "max_points": 25
              },
              {
                "key": "documentation_homepage_site",
                "name": "Documentation / homepage site",
                "detail": "https://docs.nvidia.com/nemo/automodel/nightly/index.html",
                "points": 15,
                "status": "met",
                "details": [],
                "max_points": 15
              },
              {
                "key": "repository_description",
                "name": "Repository description",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "topics",
                "name": "Topics",
                "detail": "19 topics",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "topics_count",
                    "params": {
                      "count": 19
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                  }
                ],
                "max_points": 10
              },
              {
                "key": "wiki",
                "name": "Wiki",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              }
            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
      },
      {
        "key": "security",
        "band": "moderate",
        "name": "Security",
        "value": 64,
        "weight": 0.16,
        "metrics": [
          {
            "key": "security_posture",
            "band": "moderate",
            "name": "Security posture",
            "note": "Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "branch_protection",
                    "signed_releases"
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 55,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 16,
              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 2,
              "scorecard_aggregate": 5.5
            },
            "components": [
              {
                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "branch_protection",
                "name": "Branch-Protection",
                "detail": "internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
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                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "ci_tests",
                "name": "CI-Tests",
                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 27/30 approved changesets -- score normalized to 9",
                "points": 6.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 24 contributing companies or organizations",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "no update tool detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "78 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "dependency_advisories",
            "band": "excellent",
            "name": "Dependency advisories",
            "note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:nemo-automodel@0.5.0 runtime dependency closure — what installing the published package pulls in — 131 packages. Reachability is not analyzed.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "no_advisories_left_outstanding"
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                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              },
              {
                "code": "advisories_scope_published",
                "params": {
                  "package": "pypi:nemo-automodel@0.5.0",
                  "assessed": 131
                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "source": "osv",
              "advisories": 0,
              "affected_packages": 0,
              "assessed_packages": 131,
              "unassessed_packages": 0,
              "affected_by_severity": "none",
              "direct_affected_packages": 0
            },
            "components": [
              {
                "key": "direct_dependencies_free_of_known_advisories",
                "name": "Direct dependencies free of known advisories",
                "detail": "no direct dependency carries a known advisory",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "no_direct_advisories",
                    "params": {}
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                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
              },
              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
                "detail": "no advisory carries a publication date",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "advisories_no_publication_date",
                    "params": {}
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                ],
                "max_points": 40
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            ]
          },
          {
            "key": "malicious_dependencies",
            "band": "excellent",
            "name": "Malicious dependencies",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "source": "osv",
              "meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
              "packages": [],
              "red_flag": false,
              "assessed_packages": 131,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
            },
            "components": [
              {
                "key": "no_dependency_reported_as_a_malicious_package",
                "name": "No dependency reported as a malicious package",
                "detail": "no dependency is reported as a malicious package",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "no_malicious_dependencies",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 6
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 68,
        "weight": 0,
        "metrics": [
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            "key": "ai_agent_context",
            "band": "excellent",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 85,
            "inputs": {
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              "legible_history_share": 1,
              "agent_instruction_files": [
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              "agent_instruction_max_bytes": 13233
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            "components": [
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                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "AGENTS.md, CLAUDE.md",
                "points": 45,
                "status": "met",
                "details": [
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                    "code": "file_list",
                    "params": {
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                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "100 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 100,
                      "sampled": 100
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                  }
                ],
                "max_points": 40
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            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "good",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 71,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
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              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [
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                "docs/fern/Makefile",
                "nemo_automodel/components/datasets/llm/megatron/Makefile"
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              "has_devcontainer": false,
              "has_linter_config": true,
              "typecheck_configs": [],
              "agent_commit_share": 0.24,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
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