Bumps [transformers](https://github.com/huggingface/transformers) from 4.56.1 to 5.10.1. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/huggingface/transformers/releases">transformers's releases</a>.</em></p> <blockquote> <h1>Release v5.10.1</h1> <p>v5.10.0 was yanked as we publish on a corrupted branch. Sorry everyone, this happens when we rush a release!!!</p> <h2>New Model additions</h2> <h3>Gemma4 unified+ Gemma4 MTP</h3>  <p>Gemma 4 12B Unified is an <strong>encoder-free</strong> multimodal model with pretrained and instruction-tuned variants. Unlike <a href="https://github.com/huggingface/transformers/blob/HEAD/gemma4">standard Gemma 4</a>, which uses dedicated encoder towers, Gemma 4 12B Unified projects raw inputs directly into the language model's embedding space through lightweight linear pipelines. This results in a simpler architecture while maintaining strong multimodal performance.</p> <p>Key differences from standard Gemma 4:</p> <ul> <li><strong>No Vision Tower</strong>: Raw pixel patches are projected directly into LM space via a <code>Dense + LayerNorm</code> pipeline with factorized 2D positional embeddings, replacing the vision encoder.</li> <li><strong>No Audio Tower</strong>: Raw 16 kHz waveform samples are chunked into fixed-length frames and projected through a simple <code>RMSNorm → Linear</code> pipeline, replacing the mel spectrogram + Conformer encoder.</li> <li><strong>Shared Multimodal Pipeline</strong>: Both vision and audio use the same <code>Gemma4UnifiedMultimodalEmbedder</code> (RMSNorm → Linear) for the final projection to text hidden space.</li> </ul> <p>You can find the original Gemma 4 12B Unified checkpoints under the <a href="https://huggingface.co/collections/google/gemma-4">Gemma 4</a> release.</p> <ul> <li>who needs encoders? (<a href="https://redirect.github.com/huggingface/transformers/issues/46385">#46385</a>) by <a href="https://github.com/douglas-reid"><code>@douglas-reid</code></a> <a href="https://github.com/sgerrard"><code>@sgerrard</code></a> <a href="https://github.com/vasqu"><code>@vasqu</code></a> <a href="https://github.com/molbap"><code>@molbap</code></a></li> </ul> <h3>Sapiens2</h3> <p>Sapiens2 is a family of high-resolution vision transformers pretrained on ~1 billion curated human images, designed for human-centric computer vision tasks including pose estimation, body-part segmentation, surface normal estimation, and pointmap estimation. The models scale from 0.4B to 5B parameters and train at native 1K resolution, with hierarchical 4K variants for extended spatial reasoning. Sapiens2 achieves substantial improvements over its predecessor with +4 mAP in pose estimation, +24.3 mIoU in body-part segmentation, and 45.6% error reduction in normal estimation.</p> <p><strong>Links:</strong> <a href="https://huggingface.co/docs/transformers/main/en/model_doc/sapiens2">Documentation</a> | <a href="https://huggingface.co/papers/2604.21681">Paper</a></p> <ul> <li>Add Sapiens2 Model (<a href="https://redirect.github.com/huggingface/transformers/issues/45919">#45919</a>) by <a href="https://github.com/guarin"><code>@guarin</code></a> in <a href="https://redirect.github.com/huggingface/transformers/pull/45919">#45919</a></li> </ul> <h3>DeepSeek-OCR-2</h3> <p>DeepSeek-OCR-2 is an OCR-specialized vision-language model built on a distinctive architecture that combines a SAM ViT-B vision encoder with a Qwen2 hybrid attention encoder, connected through an MLP projector to a DeepSeek-V2 Mixture-of-Experts (MoE) language model. The model features a hybrid attention mechanism that applies bidirectional attention over image tokens and causal attention over query tokens, enabling efficient and accurate document understanding. It supports both plain OCR tasks and grounding capabilities with coordinate-aware output for document conversion to markdown format.</p> <p><strong>Links:</strong> <a href="https://huggingface.co/docs/transformers/main/en/model_doc/deepseek_ocr2">Documentation</a></p> <ul> <li>Add Deepseek-OCR-2 model (<a href="https://redirect.github.com/huggingface/transformers/issues/45075">#45075</a>) by <a href="https://github.com/thisisiron"><code>@thisisiron</code></a> in <a href="https://redirect.github.com/huggingface/transformers/pull/45075">#45075</a></li> </ul> <h3>Mellum</h3> <p>Mellum is a code-focused Mixture-of-Experts language model developed by JetBrains. It is derived from the Qwen3-MoE architecture with per-layer-type RoPE and interleaved sliding window attention. The model has 12B total parameters with 2.5B active parameters per token, using 64 routed experts with 8 activated per token across 28 layers.</p> <p><strong>Links:</strong> <a href="https://huggingface.co/docs/transformers/main/en/model_doc/mellum">Documentation</a></p> <ul> <li>feat: Add support for JetBrains' <code>Mellum</code> v2 code generation model (<a href="https://redirect.github.com/huggingface/transformers/issues/46112">#46112</a>) by <a href="https://github.com/shadeMe"><code>@shadeMe</code></a> in <a href="https://redirect.github.com/huggingface/transformers/pull/46112">#46112</a></li> </ul> <h2>Breaking changes</h2> <p>The Gemma4 vision pooler now casts inputs to float32 before scaling to prevent float16 overflow (inf saturation) with large checkpoints, which may cause minor numerical differences in outputs for users running Gemma-4 vision models in float16.</p> <ul> <li>🚨 Fix float16 overflow in Gemma4 vision pooler (<a href="https://redirect.github.com/huggingface/transformers/issues/46277">#46277</a>) by <a href="https://github.com/Bluear7878"><code>@Bluear7878</code></a></li> </ul> <p>Audio Language Models (ALMs) now have a dedicated base model class without a language modeling head, aligning them with the design of Vision Language Models (VLMs); users relying on the previous model class structure should update their code to use the new base model class where appropriate.</p> <ul> <li>🚨 [ALM] Add base model without head (<a href="https://redirect.github.com/huggingface/transformers/issues/45534">#45534</a>) by <a href="https://github.com/eustlb"><code>@eustlb</code></a></li> </ul>  </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/huggingface/transformers/commit/90c3ae54d448d4906b6167317ea5a7f5d48a232d"><code>90c3ae5</code></a> Patch because we had to yank 5.10 because the release branch was not up to date</li> <li><a href="https://github.com/huggingface/transformers/commit/0bd94b37db639d8f29a094dce2fde06f86af8968"><code>0bd94b3</code></a> v5.10.0</li> <li><a href="https://github.com/huggingface/transformers/commit/1423d22f7a3b62e8c70ad67b58ec25cd9b675897"><code>1423d22</code></a> who needs encoders? (<a href="https://redirect.github.com/huggingface/transformers/issues/46385">#46385</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/50eb20a24f9dd512e6770072f422e4b86ca3cd98"><code>50eb20a</code></a> Fix dsv4 dequant + tp/ep (<a href="https://redirect.github.com/huggingface/transformers/issues/46378">#46378</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/74464e8c49c91b574c30cc3cb3c5a44000237299"><code>74464e8</code></a> Fix wrong changes produced by style/repo. check bot (<a href="https://redirect.github.com/huggingface/transformers/issues/46371">#46371</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/1b8ec344fb6c277235fc76c37e7a5c156a1f0ddc"><code>1b8ec34</code></a> Fix path traversal when saving Bark voice preset embeddings (<a href="https://redirect.github.com/huggingface/transformers/issues/46237">#46237</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/e820678256f22e7647e39e8b7ed040fa81b7b872"><code>e820678</code></a> Add Sapiens2 Model (<a href="https://redirect.github.com/huggingface/transformers/issues/45919">#45919</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/595721c44cb14db37fa504903e2edd5e9f0eba43"><code>595721c</code></a> Pass library_name/version to Hub calls via a shared HfApi (<a href="https://redirect.github.com/huggingface/transformers/issues/46318">#46318</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/0f0036c888ed81b714cb04aa6fe6689eb36bce0a"><code>0f0036c</code></a> docs: update ACL Anthology URL in CITATION.cff (<a href="https://redirect.github.com/huggingface/transformers/issues/46352">#46352</a>)</li> <li><a href="https://github.com/huggingface/transformers/commit/fa6c8308e22dade298c10c72d44937e41b962353"><code>fa6c830</code></a> DeepGEMM BF16 + mixed FP8/FP4 + MegaMoE + refactor (<a href="https://redirect.github.com/huggingface/transformers/issues/45634">#45634</a>)</li> <li>Additional commits viewable in <a href="https://github.com/huggingface/transformers/compare/v4.56.1...v5.10.1">compare view</a></li> </ul> </details> <br /> [![Dependabot compatibility score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=transformers&package-manager=pip&previous-version=4.56.1&new-version=5.10.1)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) You can trigger a rebase of this PR by commenting `@dependabot rebase`. 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 numpy == 2.1.3
 Pillow == 12.0.0
 -transformers[torch] == 4.56.1
 +transformers[torch] == 5.10.1