版本更新：huggingface/transformers v5.7.0，提升开发者接入体验

Release v5.7.0 New Model additions Laguna Laguna is Poolside's mixture-of-experts language model family that extends standard SwiGLU MoE transformers with two key innovations. It features per-layer head counts allowing different decoder layers to have different query-head counts while sharing the same KV cache shape, and implements a sigmoid MoE router with auxiliary-loss-free load balancing that uses element-wise sigmoid of gate logits plus learned per-expert bias for router scoring. Links: Documentation Laguna XS.2 implementation ( #45673 ) by @joerowell in #45673 DEIMv2 DEIMv2 (DETR with Improved Matching v2) is a real-time object detection model that extends DEIM with DINOv3 features and spans eight model sizes from X to Atto for diverse deployment scenarios. It uses a Spatial Tuning Adapter (STA) for larger variants to convert DINOv3's single-scale output into multi-scale features, while ultra-lightweight models employ pruned HGNetv2 backbones. The unified design achieves superior performance-cost trade-offs, with DEIMv2-X reaching 57.8 AP with only 50.3M parameters and DEIMv2-S being the first sub-10M model to exceed 50 AP on COCO. Links: Documentation | Paper model: Add DEIMv2 to Transformers ( #44339 ) by @harshaljanjani in #44339 Attention Several attention-related bugs were fixed across multiple models, including a cross-attention cache type error in T5Gemma2 for long inputs, incorrect cached forward behavior in Qwen3.5's gated-delta-net linear attention, and a crash in GraniteMoeHybrid when no Mamba layers are present. Attention function dispatch was also updated to align with the latest model implementations. Fix cross-attention cache layer type for T5Gemma2 long inputs ( #45540 ) by @Beichen-Ma in [ #45540 ] [Qwen3.5] Fix GDN linear attention multi-token cached forward ( #45513 ) by @kashif in [ #45513 ] Fix GraniteMoeHybrid _update_mamba_mask crash on attention-only models ( #45514 ) by @tianhaocui in [ #45514 ] Align latest model attention function dispatch ( #45598 ) by @Cyrilvallez in [ #45598 ] Tokenizers There was a bug in AutoTokenizer that caused the wrong tokenizer class to be initialized. This caused regressions in models like DeepSeek R1. change got reverted ( #45680 ) by @itazap in [ #45680 ] Generation Continuous batching generation received several fixes and improvements, including correcting KV deduplication and memory estimation for long sequences (16K+), and removing misleading warnings about num_return_sequences and other unsupported features that were incorrectly firing even when functionality worked correctly. Documentation for per-request sampling parameters was also added. generate: drop stale num_return_sequences warning on continuous batching path ( #45582 ) by @joaquinhuigomez in [ #45582 ] Remove unnecessary generate warnings ( #45619 ) by @Cyrilvallez in [ #45619 ] [CB] Changes for long generation ( #45530 ) by @remi-or in [ #45530 ] [docs] per-request sampling params ( #45553 ) by @stevhliu in [ #45553 ] Kernels Improved kernel support by fixing configuration reading and error handling for FP8 checkpoints (e.g., Qwen3.5-35B-A3B-FP8), enabling custom expert kernels registered from the HF Hub to be properly loaded, and resolving an incompatibility that prevented Gemma3n and Gemma4 from using the rotary kernel. Fix configuration reading and error handling for kernels ( #45610 ) by @hmellor in [ #45610 ] Allow for registered experts from kernels hub ( #45577 ) by @winglian in [ #45577 ] Gemma3n and Gemma4 cannot use rotary kernel ( #45564 ) by @Cyrilvallez in [ #45564 ] Bugfixes and improvements fixing more typos ( #45689 ) by @vasqu in [ #45689 ] [docs] cb memory management ( #45587 ) by @stevhliu in [ #45587 ] [docs] cpu offloading ( #45660 ) by @stevhliu in [ #45660 ] docs(README_zh-hans): clarify conditions for not using Transformers ( #45688 ) by @GuaiZai233 in [ #45688 ] fix padding side issue for fast_vlm tests ( #45592 ) by @kaixuanliu in [ #45592 ] Fix x_clip : 8 failed test cases ( #45394 ) by @kaixuanliu in [ #45394 ] zero_shot_object_detection ValueError fix for python 3.13 ( #45669 ) by @AnkitAhlawat7742 in [ #45669 ] Fix pageable H2D copies in Gated DeltaNet PyTorch fallback ( #45665 ) by @ruixiang63 in [ #45665 ] Fix UnboundLocalError in shard_and_distribute_module for replicated parameters ( #45675 ) by @Abdennacer-Badaoui in [ #45675 ] [MistralCommonBackend] Soften validation mode and apply_chat_template arguments check ( #45628 ) by @juliendenize in [ #45628 ] Fix NameError: PeftConfigLike triggered by PreTrainedModel.__init_subclass__ ( #45658 ) by @qgallouedec in [ #45658 ] chore(typing): added modeling_utils to ty ( #45425 ) by @tarekziade in [ #45425 ] [gemma4] infer from config instead of hardcoding ( #45606 ) by @eustlb in [ #45606 ] Update quants tests ( #45480 ) by @SunMarc in [ #45480 ] 🔴🔴🔴 fix: skip clean_up_tokenization for BPE tokenizers in PreTrainedTokenizerFast ( #44915 ) by @maxsloef-goodfire in [ #44915 ] Fix colmodernvbert tests ( #45652 ) by @Cyrilvallez in [ #45652 ] [CB] [Major] Add CPU request offloading ( #45184 ) by @remi-or in [ #45184 ] Fix peft constructors ( #45622 ) by @Cyrilvallez in [ #45622 ] chore: speedup modular converter (~30%) ( #45046 ) by @tarekziade in [ #45046 ] Fix whisper return language ( #42227 ) by @FredHaa in [ #42227 ] Add supports_gradient_checkpointing to NemotronHPreTrainedModel ( #45625 ) by @sergiopaniego in [ #45625 ] Raise clear error for problem_type="single_label_classification" with num_labels=1 ( #45611 ) by @gaurav0107 in [ #45611 ] CircleCI with torch 2.11 ( #45633 ) by @ydshieh in [ #45633 ] chore: bump doc-builder SHA for main doc build workflow ( #45631 ) by @rtrompier in [ #45631 ] Allow more artifacts to be download in CI ( #45629 ) by @ydshieh in [ #45629 ] chore(qa): split pipeline and add type checking ( #45432 ) by @tarekziade in [ #45432 ] Skip failing offloading tests ( #45624 ) by @Cyrilvallez in [ #45624 ] fix: compute auxiliary losses when denoising is disabled in D-FINE ( #45601 ) by @Abineshabee in [ #45601 ] qa: bumped mlinter and allow local override ( #45585 ) by @tarekziade in [ #45585 ] Processing Utils: continue when content is a string ( #45605 ) by @RyanMullins in [ #45605 ] SonicMoe ( #45433 ) by @IlyasMoutawwakil in [ #45433 ] fix transformers + torchao nvfp4 serialization ( #45573 ) by @vkuzo in [ #45573 ] [AMD CI] Fix expectations for Gemma3n ( #45602 ) by @Abdennacer-Badaoui in [ #45602 ] [docs] multi-turn tool calling ( #45554 ) by @stevhliu in [ #45554 ] Fix AttributeError on s_aux=None in flash_attention_forward ( #45589 ) by @jamesbraza in [ #45589 ] do not index past decoded chars with special tokens ( #45435 ) by @itazap in [ #45435 ] Update dev version ( #45583 ) by @vasqu in [ #45583 ] Update torchao usage for XPU and CPU ( #45560 ) by @jiqing-feng in [ #45560 ] Significant community contributions The following contributors have made significant changes to the library over the last release: @vasqu fixing more typos ( #45689 ) Update dev version ( #45583 ) @joerowell Laguna XS.2 implementation ( #45673 ) @tarekziade chore(typing): added modeling_utils to ty ( #45425 ) chore: speedup modular converter (~30%) ( #45046 ) chore(qa): split pipeline and add type checking ( #45432 ) qa: bumped mlinter and allow local override ( #45585 ) @harshaljanjani model: Add DEIMv2 to Transformers ( #44339 ) @remi-or [CB] [Major] Add CPU request offloading ( #45184 ) [CB] Changes for long generation ( #45530 )