chore(deps): bump transformers from 5.10.2 to 5.11.0

[dependabot]

Bumps transformers from 5.10.2 to 5.11.0.

Release notes

Sourced from transformers's releases.

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

... (truncated)

Commits

• e7b5b96 v5.11.0
• 513146c Add deepseek 3.2 exp (#41251)
• 6de6661 GPU go brr (#46540)
• 33b7e4f [docs] 4D attention masks (#46507)
• b0a38eb Fix the offsets in processing (#46525)
• c1b6e83 Fix buggy action sha pin (#46534)
• 0095551 Fix trailing comma bug in DataCollatorForLanguageModeling example (#46527)
• 04cb96f Fix missing Gemma4Processor._compute_audio_num_tokens (#46416)
• d557ef5 Fix InternVL models (#46524)
• d209460 fix(afmoe): reduce tokens in test_compile_static_cache to avoid flaky bfloat1...
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