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Transformers

v5.11.0 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

Published 1mo LLM Frameworks
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

audio machine-learning deepseek gemma glm llm
+11 more
model-hub natural-language-processing nlp pretrained-models python pytorch pytorch-transformers qwen speech-recognition transformer vlm

Summary

AI summary

Broad release touches Bugfixes and improvements, New Model additions, ci, and fix.

Changes in this release

Feature Low

Adds DiffusionGemma model for faster inference using encoder-decoder architecture.

Adds DiffusionGemma model for faster inference using encoder-decoder architecture.

Source: llm_adapter@2026-06-10

Confidence: high

Feature Low

Adds DeepSeek-V3.2-Exp with DeepSeek Sparse Attention for efficient long-context processing.

Adds DeepSeek-V3.2-Exp with DeepSeek Sparse Attention for efficient long-context processing.

Source: llm_adapter@2026-06-10

Confidence: high

Feature Low

Extends KernelConfig API to support n-to-1 module fusion and parameter transformation.

Extends KernelConfig API to support n-to-1 module fusion and parameter transformation.

Source: llm_adapter@2026-06-10

Confidence: high

Feature Low

Adds fine‑grained fp8/fp4 Triton kernel support.

Adds fine‑grained fp8/fp4 Triton kernel support.

Source: llm_adapter@2026-06-10

Confidence: high

Feature Low

Adds `max_requests_per_batch` parameter to CB component.

Adds `max_requests_per_batch` parameter to CB component.

Source: llm_adapter@2026-06-10

Confidence: high

Bugfix Medium

Fixes dtype mismatch in NemotronH/Zamba2 Mamba2 CUDA kernel path.

Fixes dtype mismatch in NemotronH/Zamba2 Mamba2 CUDA kernel path.

Source: llm_adapter@2026-06-10

Confidence: high

Bugfix Medium

Updates FalconMamba fast‑path warning to recommend `pip install kernels`.

Updates FalconMamba fast‑path warning to recommend `pip install kernels`.

Source: llm_adapter@2026-06-10

Confidence: high

Bugfix Medium

Fixes model parallel beam search bugs in Qwen2‑VL, Qwen2.5‑VL, and Qwen3‑VL MoE families.

Fixes model parallel beam search bugs in Qwen2‑VL, Qwen2.5‑VL, and Qwen3‑VL MoE families.

Source: llm_adapter@2026-06-10

Confidence: high

Bugfix Medium

Fixes regression introduced by #45534.

Fixes regression introduced by #45534.

Source: llm_adapter@2026-06-10

Confidence: high

Bugfix Medium

Adds documentation for tensor parallelism support with continuous batching.

Adds documentation for tensor parallelism support with continuous batching.

Source: llm_adapter@2026-06-10

Confidence: low

Full changelog

Release v5.11.0

New Model additions

DiffusionGemma

DiffusionGemma is engineered to reduce the sequential bottlenecks of standard causal language models by employing an encoder-decoder architecture specifically optimized for inference speed. During inference, DiffusionGemma leverages multi-canvas sampling, where rather than generating one token at a time, the model iteratively denoises a full block of tokens using a diffusion sampler. This block-autoregressive approach facilitates text generation at higher speeds compared to traditional sequential generation methods.

Links: Documentation

  • GPU go brr (#46540) by @gante in #46540

DeepSeek-V3.2

DeepSeek-V3.2-Exp is an experimental model from DeepSeek-AI that introduces DeepSeek Sparse Attention (DSA), a trainable, fine-grained sparse attention mechanism designed to improve training and inference efficiency in long-context scenarios. Built on top of DeepSeek-V3.1-Terminus with a 685B-parameter Mixture-of-Experts backbone, it reduces the quadratic cost of attention over long sequences by attending only to a selected subset of past tokens while maintaining virtually identical benchmark performance. The work was extended in DeepSeek-V3.2 which pairs DSA with scalable reinforcement learning and achieves gold-medal level results on competition math and competitive programming benchmarks.

Links: Documentation | Paper

  • Add deepseek 3.2 exp (#41251) by @ArthurZucker in #41251

Kernels

The KernelConfig API was extended to support n-to-1 module fusion and parameter transformation, simplifying how custom kernels are integrated with Transformers modules. Additional fixes include resolving a dtype mismatch in the Mamba2 CUDA kernel path for NemotronH/Zamba2, adding fine-grained fp8/fp4 Triton kernel support, and correcting the FalconMamba fast-path warning to recommend pip install kernels instead of mamba-ssm.

  • Extended & simplified n-to-1 kernel fusion via KernelConfig (#46339) by @michaelbenayoun in [#46339]
  • Triton finegrained fp8/fp4 (#46407) by @IlyasMoutawwakil in [#46407]
  • Fix dtype mismatch in NemotronH/Zamba2 Mamba2 CUDA-kernel path (out_proj) (#46487) by @yuekaizhang in [#46487]
  • fix(falcon_mamba): recommend pip install kernels in fast-path warning (#46343) by @Anai-Guo in [#46343]

Parallelization

Fixed model parallel beam search bugs in the Qwen2-VL, Qwen2.5-VL, and Qwen3-VL MoE model families, and added documentation for tensor parallelism support with continuous batching.

  • [docs] tp for continuous batching (#46019) by @stevhliu in [#46019]
  • revisit history parallel beam search tests to avoid unnecessary fix (#46495) by @kaixuanliu in [#46495]
  • fix qwen series VL model's model parallel bug (#46316) by @kaixuanliu in [#46316]

Bugfixes and improvements

  • Fix the offsets in processing (#46525) by @zucchini-nlp in [#46525]
  • Fix buggy action sha pin (#46534) by @ydshieh in [#46534]
  • Fix trailing comma bug in DataCollatorForLanguageModeling example (#46527) by @JemmaUZH in [#46527]
  • Fix missing Gemma4Processor._compute_audio_num_tokens (#46416) by @csantosbh in [#46416]
  • Fix InternVL models (#46524) by @hmellor in [#46524]
  • fix(afmoe): reduce tokens in test_compile_static_cache to avoid flaky bfloat16 drift (#46521) by @ydshieh in [#46521]
  • [CB] Add a "max_requests_per_batch" parameter (#46434) by @remi-or in [#46434]
  • revamp cv docs and fix rf-detr (#46219) by @merveenoyan in [#46219]
  • Update hub metadata (#46379) by @zucchini-nlp in [#46379]
  • extend DeepseekV4FlashIntegrationTest to non-cuda device (#46517) by @sywangyi in [#46517]
  • [docs] deepgemm (#46361) by @stevhliu in [#46361]
  • [fix] regression introduced by #45534 (#46456) by @eustlb in [#46456]
  • Use torchvision's native LANCZOS interpolation instead of PIL fallback (#46496) by @NicolasHug in [#46496]
  • Add debugging info in pr-ci-caller.yml (#46505) by @ydshieh in [#46505]
  • Fix tests: 'Cohere2MoeModel' object has no attribute 'hf_device_map' (#46337) by @kaixuanliu in [#46337]
  • Bump the actions group across 1 directory with 19 updates (#46414) by @dependabot[bot] in [#46414]
  • Log some information in .github/workflows/pr-ci-post-dashboard-link.yml (#46499) by @ydshieh in [#46499]
  • feat(quantizers): support non-weight param names in TorchAo safetensors loading (#46325) by @agesf in [#46325]
  • docs: fix typo in make_list_of_images docstring (#46469) by @ramkumar27072006 in [#46469]
  • add XPU expectation for deepseek_ocr2 model tests (#46492) by @kaixuanliu in [#46492]
  • Fix sapiens2 tests: add XPU device expectations (#46488) by @kaixuanliu in [#46488]
  • Add vLLM smoke test to CI (#46383) by @hmellor in [#46383]
  • extend deepseek v4 test to xpu (#46366) by @sywangyi in [#46366]
  • Added cosmos3 model (#46146) by @MaciejBalaNV in [#46146]
  • fbgemm_fp8:Keep the current device aligned with the input tensor (#46403) by @kaixuanliu in [#46403]
  • [Modular] Add no_inherit_decorators and fixup wrong RoPE related inheritances (#46440) by @Bissmella in [#46440]
  • skip deepgemm test except cuda (#46090) by @jiqing-feng in [#46090]
  • Fix/video classification pipeline video processor (#46256) by @J3r3myPerera in [#46256]
  • ci: less flaky test_assisted_decoding_matches_greedy_search_1_same (#46445) by @ydshieh in [#46445]
  • Fix flip_back graph break (#46344) by @guarin in [#46344]
  • Add the other processors to auto-mappings (#46046) by @zucchini-nlp in [#46046]
  • fix: compatibility with torch<=2.7 (#46393) by @andylin-hao in [#46393]
  • fix: remove dynamic per-actor Slack ID lookup in ssh-runner workflow (#46327) by @ydshieh in [#46327]
  • [docs] Romanian translation of pipeline_tutorial.md, pipeline_gradio.md, pipeline_webserver.md and add_new_pipeline.md. (#46388) by @filipinescu in [#46388]
  • [docs] gemma4 typos (#46351) by @stevhliu in [#46351]
  • [docs] padding-free training (#46333) by @stevhliu in [#46333]
  • fix[vLLM x v5]: Default untied embeddings in AudioFlamingo3 and VibeVoice (#46400) by @harshaljanjani in [#46400]
  • Fix deepspeed docker (#46108) by @SunMarc in [#46108]
  • Fix conversion for clip models (#46406) by @zucchini-nlp in [#46406]
  • ci: mention code quality failure in CI dashboard comment (#46415) by @ydshieh in [#46415]
  • Fix noisy logging from image_processing module aliases issue - 46298 (#46350) by @skshmjn in [#46350]
  • Raise tqdm minimum to 4.60 to match tqdm.contrib.logging import (#46397) by @n0gu-furiosa in [#46397]
  • fix(gemma4_unified): conversion script and config bugs (#46398) by @douglas-reid in [#46398]
  • [docs] remove sparsity from compressed-tensors (#46387) by @stevhliu in [#46387]
  • [CB] Fix crashes when fork is not possible (#46251) by @remi-or in [#46251]
  • Improve CI dashboard comment: rename and deduplicate (#46412) by @ydshieh in [#46412]
  • Fix missing f-string prefixes in error messages (#46354) by @joaopedroassad in [#46354]
  • Add workflow to post CI Grafana dashboard link to PR (#46410) by @ydshieh in [#46410]
  • [docs] Romanian translation of fast_tokenizers.md, custom_tokenizers.md, tokenizer_summary.md, image_processors.md and video_processors.md. (#46356) by @filipinescu in [#46356]
  • Clean up new models after release (#46092) by @zucchini-nlp in [#46092]

Significant community contributions

The following contributors have made significant changes to the library over the last release:

  • @ArthurZucker
    • Add deepseek 3.2 exp (#41251)
  • @gante
    • GPU go brr (#46540)
  • @merveenoyan
    • revamp cv docs and fix rf-detr (#46219)
  • @sgerrard
    • Quantization for small models (#46449)
  • @MaciejBalaNV
    • Added cosmos3 model (#46146)
  • @J3r3myPerera
    • Fix/video classification pipeline video processor (#46256)
  • @filipinescu
    • [docs] Romanian translation of pipeline_tutorial.md, pipeline_gradio.md, pipeline_webserver.md and add_new_pipeline.md. (#46388)
    • [docs] Romanian translation of fast_tokenizers.md, custom_tokenizers.md, tokenizer_summary.md, image_processors.md and video_processors.md. (#46356)

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Related context

Earlier breaking changes

  • v5.9.0 `text_embeds` input for SAM3, EdgeTAM, and SAM3-Lite-Text now expects full text embeddings instead of pooler outputs.

Beta — feedback welcome: [email protected]