chore(deps): update dependency transformers to v5#65
Open
red-hat-konflux[bot] wants to merge 1 commit intopoc1from
Open
chore(deps): update dependency transformers to v5#65red-hat-konflux[bot] wants to merge 1 commit intopoc1from
red-hat-konflux[bot] wants to merge 1 commit intopoc1from
Conversation
|
Important Review skippedBot user detected. To trigger a single review, invoke the You can disable this status message by setting the Comment |
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
from
16de9c8 to
b9d3be5
Compare
ruivieira
pushed a commit
that referenced
this pull request
Feb 9, 2026
Fixing Tier 1 - Hugging Face Runtime unit tests
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
from
b9d3be5 to
b95b05b
Compare
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
from
b95b05b to
23acd25
Compare
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
2 times, most recently
from
cba6ffa to
21708c3
Compare
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
3 times, most recently
from
aee6daa to
34190a2
Compare
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
2 times, most recently
from
449600b to
a670065
Compare
Signed-off-by: red-hat-konflux <126015336+red-hat-konflux[bot]@users.noreply.github.com>
red-hat-konflux
Bot
force-pushed
the
konflux/mintmaker/poc1/transformers-5.x
branch
from
a670065 to
9d2f638
Compare
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This PR contains the following updates:
==4.57.1→==5.6.2Release Notes
huggingface/transformers (transformers)
v5.6.2: Patch release v5.6.2Compare Source
Patch release v5.6.2
Qwen 3.5 and 3.6 MoE (text-only) were broken when using with FP8. It should now work again with this 🫡
Full Changelog: huggingface/transformers@v5.6.1...v5.6.2
v5.6.1: Patch release v5.6.1Compare Source
Patch release v5.6.1
Flash attention path was broken! Sorry everyone for this one 🤗
v5.6.0Compare Source
Release v5.6.0
New Model additions
OpenAI Privacy Filter
OpenAI Privacy Filter is a bidirectional token-classification model for personally identifiable information (PII) detection and masking in text. It is intended for high-throughput data sanitization workflows where teams need a model that they can run on-premises that is fast, context-aware, and tunable. The model labels an input sequence in a single forward pass, then decodes coherent spans with a constrained Viterbi procedure, predicting probability distributions over 8 privacy-related output categories for each input token.
Links: Documentation
Privacy Filter] Add model (#45580) by @vasqu in #45580QianfanOCR
Qianfan-OCR is a 4B-parameter end-to-end document intelligence model developed by Baidu that performs direct image-to-text conversion without traditional multi-stage OCR pipelines. It supports a broad range of prompt-driven tasks including structured document parsing, table extraction, chart understanding, document question answering, and key information extraction all within one unified model. The model features a unique "Layout-as-Thought" capability that generates structured layout representations before producing final outputs, making it particularly effective for complex documents with mixed element types.
Links: Documentation | Paper
SAM3-LiteText
SAM3-LiteText is a lightweight variant of SAM3 that replaces the heavy SAM3 text encoder (353M parameters) with a compact MobileCLIP-based text encoder optimized through knowledge distillation, while keeping the SAM3 ViT-H image encoder intact. This reduces text encoder parameters by up to 88% while maintaining segmentation performance comparable to the original model. The model enables efficient vision-language segmentation by addressing the redundancy found in text prompting for segmentation tasks.
Links: Documentation | Paper
SLANet
SLANet and SLANet_plus are lightweight models designed for table structure recognition, focusing on accurately recognizing table structures in documents and natural scenes. The model improves accuracy and inference speed by adopting a CPU-friendly lightweight backbone network PP-LCNet, a high-low-level feature fusion module CSP-PAN, and a feature decoding module SLA Head that aligns structural and positional information. SLANet was developed by Baidu PaddlePaddle Vision Team as part of their table structure recognition solutions.
Links: Documentation
Breaking changes
The internal
rotary_fnis no longer registered as a hidden kernel function, so any code referencingself.rotary_fn(...)within an Attention module will break and must be updated to call the function directly instead.Kernels] Fix kernel function registration (#45420) by @vasquServe
The
transformers servecommand received several enhancements, including a new/v1/completionsendpoint for legacy text completion, multimodal support for audio and video inputs, improved tool-calling viaparse_response, proper forwarding oftool_calls/tool_call_idfields, a 400 error on model mismatch when the server is pinned to a specific model, and fixes for the response API. Documentation was also updated to cover new serving options such as--compileand--model-timeout.transformers serve(#44558) by @rain-1 in [#44558]transformers serveis pinned (#45443) by @qgallouedec in [#45443]parse_response(#45485) by @SunMarc in [#45485]tool_calls/tool_call_idin processor inputs (#45418) by @qgallouedec in [#45418]Vision
Several vision-related bug fixes were applied in this release, including correcting Qwen2.5-VL temporal RoPE scaling for still images, fixing missing/mismatched image processor backends for Emu3 and BLIP, resolving modular image processor class duplication, and preventing accelerate from incorrectly splitting vision encoders in PeVideo/PeAudioVideo models. Image loading performance was also improved by leveraging torchvision's native
decode_imagein the torchvision backend, yielding up to ~17% speedup over PIL-based loading.decode_imageto load images in the torchvision backend (#45195) by @yonigozlan in [#45195]Parallelization
Fixed several bugs affecting distributed training, including silently wrong results or NaN loss with Expert Parallelism, NaN weights on non-rank-0 FSDP processes, and a resize failure in PP-DocLayoutV3; additionally added support for loading adapters with Tensor Parallelism, added MoE to the Gemma4 TP plan, and published documentation for TP training.
Tokenization
Fixed a docstring typo in streamer classes, resolved a Kimi-K2.5 tokenizer regression and
_patch_mistral_regexAttributeError, and patched a streaming generation crash forQwen3VLProcessorcaused by incorrect_tokenizerattribute access. Additional housekeeping included moving the GPT-SW3 instruct tokenizer to an internal testing repo and fixing a global state leak in the tokenizer registry during tests.Tokenizers] Move gpt sw3 tokenizer out (#45404) by @vasqu in [#45404]test_processors(#45318) by @tarekziade in [#45318]Cache
Cache handling was improved for Gemma4 and Gemma3n models by dissociating KV state sharing from the Cache class, ensuring KV states are always shared regardless of whether a Cache is used. Additionally, the image cache for Paddle models was updated to align with the latest API.
Audio
Audio models gained vLLM compatibility through targeted fixes across several model implementations, while reliability improvements were also made including exponential back-off retries for audio file downloads, a crash fix in the
text-to-speechpipeline when generation configs containNonevalues, and corrected test failures for Kyutai Speech-To-Text.text-to-speechpipeline crash when generation config containsNonevalues (#45107) by @jiqing-feng in [#45107]Bugfixes and improvements
Privacy Filter] Add model (#45580) by @vasqu in [#45580]pass(inherits from DSV3 MoE) (#45572) by @casinca in [#45572]DeepseekV3MoEand remote official implementation (#45441) by @casinca in [#45441]prepare_decoder_input_ids_from_labels(#45516) by @Tokarak in [#45516]TextToAudioPipelinemissing<bos>token (#45525) by @jiqing-feng in [#45525]Conversion Mapping] Small fixups (#45483) by @vasqu in [#45483]get_image_sizemethod (#45461) by @JiauZhang in [#45461]fix] Always early return for non-Mistral models in _patch_mistral_regex (#45444) by @tomaarsen in [#45444]fix] Make Qwen2_5OmniProcessor warning a lot less noisy via warning_once (#45455) by @tomaarsen in [#45455]step3_vltoMODELS_WITH_INCORRECT_HUB_TOKENIZER_CLASS(#45449) by @hmellor in [#45449]fix] PEFT integration fixes preventing save/load & integration (#45428) by @tomaarsen in [#45428]apply_chat_templatecrash ontool_callmessages without content (#45348) by @qgallouedec in [#45348]trackiointegration to use Buckets and "freeze" Space after training (#45329) by @abidlabs in [#45329]cohere_asr: fix device issue fortest_model_parallel_beam_search(#45214) by @kaixuanliu in [#45214][transformers]prefix in non-verbose mode (#45316) by @zucchini-nlp in [#45316]pi0model (#45011) by @kaixuanliu in [#45011]grouped_mm(#45001) by @Sai-Suraj-27 in [#45001]Wav2Vec2Config.vocab_sizetype to allowNone(#45108) by @jiqing-feng in [#45108]hasattr(torch.backends.cudnn, "conv")toconftest.py(#45263) by @ydshieh in [#45263]SmolVLMvideo processorresizeusing wrong interpolation after backend refactor (#45258) by @ydshieh in [#45258]Qwen2IntegrationTest(#45268) by @ydshieh in [#45268]torch.backends.cudnn.conv.fp32_precisionexplicitly. (#45248) by @ydshieh in [#45248]torch 2.11(#45243) by @ydshieh in [#45243]get_test_info.py(related to tiny model creation) (#45238) by @ydshieh in [#45238]test_register_result_handler(#45188) by @SunMarc in [[#45188](https://redirect.github.com/huggingface/Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.
To execute skipped test pipelines write comment
/ok-to-test.Documentation
Find out how to configure dependency updates in MintMaker documentation or see all available configuration options in Renovate documentation.