Hugging Face Release Notes
75 release notes curated from 3 sources by the Releasebot Team. Last updated: Aug 13, 2026
Hugging Face Products
- Aug 12, 2026
- Date parsed from source:Aug 12, 2026
- First seen by Releasebot:Aug 13, 2026
Aug 12, 26
Hugging Face adds per-resource-group feature access controls for more flexible permissions across Jobs, Inference Endpoints, and blog publishing.
You can now control feature access per resource group rather than across the whole organization. Before, the only way to limit a feature was by organization role.
This means you can leave Jobs open to everyone, restrict Inference Endpoints to admins, and give blog publishing rights only to the blog-writer resource group users.
Original source - Aug 10, 2026
- Date parsed from source:Aug 10, 2026
- First seen by Releasebot:Aug 11, 2026
Release: v5.15.0
transformers releases v5.15.0 with new model support, including Meta Muse Glimmer and Granite, AXK1 and AXK2, Cosmos3 Edge, plus broader attention, vision, audio, cache, quantization, tokenizer, serving, and parallelization improvements with many bug fixes and breaking API updates.
Release v5.15.0
New Model additions
Meta Muse Glimmer
Muse Glimmer, released today, is Meta’s new multimodal model, especially designed for agentic use cases. Distilled from Muse to 30B parameters, and released under the Apache 2.0 license, it can be deployed to local setups for privacy-aware applications such as coding, document analysis, personal assistants, Claw- or Hermes-like setups.
Muse Glimmer is a dense 30B parameter model consisting of:
- 2B ViT-style encoder for vision (Perception Encoder)
- 28B parameter text decoder
We're covering it in the following blogpost: http://hf.co/blog/muse-glimmer
GraniteMoeSWA & GraniteSWA
Links: Documentation
Add Granite-swa and Granitemoe-swa model support (#47179) by @daviswer in #47179
Links: Documentation
Add Granite-swa and Granitemoe-swa model support (#47179) by @daviswer in #47179
A.X-K1 & A.X-K2
Links: Documentation
Add AXK2 from SKT (#47528) by @vasqu in #47528
Links: Documentation
add_axk1 (#46867) by @kmswin1 in #46867
Cosmos3 Edge
Links: Documentation
Add Cosmos3 Edge model support (#47181) by @atharvajoshi10 in #47181
Breaking changes
Kernels are now opt-in rather than mandatory for linear attention models (Mamba, GDN, Conv-only, etc.), so users who relied on automatic kernel selection must explicitly enable kernels to maintain previous behavior.
🚨 [Kernels] Refactor all linear attn models & native kernels fallback (#47630) by @vasqu
The cache cropping API now only accepts negative values (relative offsets) instead of absolute sizes, so users calling crop methods directly must update their code to pass negative values accordingly.
🚨 [cache] Cropping can only be done with negative values (#47720) by @Cyrilvallez
T5 and its model family (MT5, LongT5, etc.) now support SDPA and other attention backends via ALL_ATTENTION_FUNCTIONS, meaning the default attention implementation may change and users relying on the previous eager-only path should explicitly set attn_implementation="eager" if needed.
🚨 Enable SDPA (and other attention backends) for T5 and propagate to the T5 family (#47014) by @jiqing-feng
Several small private helper functions (e.g., _is_url, _build_image_tokens) have been removed from multimodal processor files, so users or downstream libraries that imported these private functions directly must remove or replace those references.
🚨 Processors update the rest (#46556) by @zucchini-nlp
Attention
This release includes several attention fixes and improvements, including correcting Multi-Head Latent Attention (MLA) cache compression, optimizing Flash Attention max sequence length computation in vision models, and fixing bugs in CTRL flex-attention and SDPA prefill with position bias. Additional changes refactor linear attention models for better maintainability, make Gemma 4's heterogeneous attention config explicit, and improve MPS support via metal-flash-sdpa integration.
[Fix] Fix multi-head latent attention (MLA) (#47761) by @remi-or in [#47761]
Refactor all linear attention models to latest best standards for convolution (#47452) by @Cyrilvallez in [#47452]
Allow metal-flash-sdpa for OpenAIPrivacyFilter on MPS (#46740) by @ArthurZucker in [#46740]
Use new per_layer_config for Gemma 4 so that heterogeneous attention config is explicit (#47384) by @hmellor in [#47384]
add paged attention tests support for XPU (#47163) by @kaixuanliu in [#47163]
Move value padding into the attention interfaces that need it (#47451) by @hmellor in [#47451]
Simplify function dispatch for linear attention (#47450) by @Cyrilvallez in [#47450]
Optimize flash attention max seqlen computation in vision attention (#47170) by @ShareLer in [#47170]
Fix BlockMask crash in CTRL flex-attention generation (#46854) by @jiqing-feng in [#46854]
[CB] Automatically switch attention implementation to flash (#47330) by @remi-or in [#47330]
Fix sdpa prefill with position_bias (#47359) by @Cyrilvallez in [#47359]
Vision
Vision improvements in this release include performance optimizations such as faster image preprocessing for vision-language models (GLM4V, MiniMaxM3-VL, and others) by eliminating redundant tensor copies, and more efficient Flash Attention variable-length paths by precomputing maximum sequence lengths once per forward pass. Several bug fixes were also applied, including correcting dtype alignment in Kosmos2/Kosmos2_5 embedding merges, fixing a position-embedding initialization fallback in Phi4Multimodal, resolving PIL resize parity in Hunyuan-VL, and patching stop-sequence handling in the image-text-to-text pipeline.
Modularize qwen-format vision processors (#47573) by @zucchini-nlp in [#47573]
Update daily CI Docker image to torch 2.13.0 / CUDA 13.0 (#47738) by @ydshieh in [#47738]
Align image feature dtype in kosmos2 and kosmos2_5 embedding merge (#47691) by @ in [#47691]
Speed up image preprocessing for vision-language models (#47453) by @labAxiaoming in [#47453]
Fix vision position-embedding init width fallback in Phi4Multimodal (#47509) by @ in [#47509]
Fix Hunyuan-VL PIL image resize parity with reference preprocessing (#47233) by @IMvision12 in [#47233]
Fix image-text-to-text stop_sequence handling (#47032) by @Sunt-ing in [#47032]
Refactor image loading in tests to use load_test_image helper (#47218) by @LevelVoid in [#47218]
Generation
Several generation improvements and bug fixes were made, including enabling batched audio generation for Qwen2.5/3-Omni, allowing sliding window cache layers to work with speculative decoding, and fixing memory overhead from static cache persistence across generate() calls. Multiple model-specific bugs were also resolved, including crashes in KyutaiSpeechToText, MusicgenForCausalLM, CTRL flex-attention, and assisted decoding for EncoderDecoder cache and OlmoHybrid models.
Align OlmoHybrid to use a native cache in generate (#47604) by @Cyrilvallez in [#47604]
[generate] Stop setting the static cache as an attribute to save memory (#47731) by @Cyrilvallez in [#47731]
Add support for batched Qwen2.5/3-Omni audio generation (#47186) by @IMvision12 in [#47186]
[cache] Allow sliding window layers to be roll-backed for speculative decoding (#47447) by @Cyrilvallez in [#47447]
Fix shape mismatch in KyutaiSpeechToText generate() last window (#46952) by @jiqing-feng in [#46952]
Fix typo in MusicgenForCausalLM.generate() (#46974) by @jiqing-feng in [#46974]
Fix assisted decoding for models with EncoderDecoder cache & OlmoHybrid (#47361) by @Cyrilvallez in [#47361]
Cache
Several cache-related bugs were fixed, including correcting NemotronH's missing "mlp" layer-type mapping, resolving recurrent-layer padding masks being skipped during chunked prefill and cache continuation for hybrid models, and fixing assisted decoding for models with EncoderDecoderCache and OlmoHybrid. Additional improvements include aligning OlmoHybrid to use a native cache, enabling sliding window layers to support speculative decoding rollback, and stopping the static cache from being stored as a model attribute to reduce unexpected memory overhead.
[docs] MPS graph cache (#47304) by @stevhliu in [#47304]
Fix NemotronH: Register "mlp" in the cache layer-type mappings (#47535) by @qgallouedec in [#47535]
Fix recurrent-layer padding mask being skipped on continued forwards (chunked prefill, cache continuation) (#47087) by @abcgco in [#47087]
Kernels
⚠️ The kernels python package will very likely be a required dependency for transformers[torch] in the near future. This will help us deliver maximum performance to all users; kernels will only be downloaded from trusted publishers manually approved by the HF team. Please let us know of any issues you're facing beforehands so that we may solidify our integration.
Improved robustness of the kernels integration by refactoring function handling to use layer repos, fixing CI EROFS fallback patches for kernel downloads via HfApi, resolving a positional argument collision in causal_conv1d_fn, and bumping the FP8 kernels version to prevent NaNs.
[conftest] Fix EROFS fallback for kernel downloads (correct interception point) (#47794) by @ydshieh in [#47794]
[conftest] Fix EROFS fallback for kernel downloads via HfApi (#47791) by @ydshieh in [#47791]
[Kernels] Refactor function handling (#46883) by @vasqu in [#46883]
Kernels and loaders robustification (#47334) by @IlyasMoutawwakil in [#47334]
Fix causal_conv1d_fn positional activation colliding with hub kernel's seq_idx (#47527) by @qgallouedec in [#47527]
[FP8] Bump kernels version (#47344) by @vasqu in [#47344]
[docs] FlashAttention kernel fallback (#47345) by @stevhliu in [#47345]
Quantization
Quantization support was expanded with FP8 kernels for compressed-tensors models, fixes for FP8 module normalization and format-based compression detection, and a multi-device MXFP4 dequantization race condition fix. GPTQ and MXFP4 tests were also extended to cover Intel XPU devices.
extend tests/quantization/gptq/test_gptq.py::GPTQTestCUDA and tests/q… (#47166) by @sywangyi in [#47166]
Compressed tensors fp8 (#47216) by @SunMarc in [#47216]
Fix A.X-K2 fp8 modules_to_not_convert normalization for the gated-norm MLP (#47578) by @kmswin1 in [#47578]
[Quantization]: Refactor is_quantization_compressed for format-based detection (#47152) by @rigen1048 in [#47152]
Fix multi-device mxfp4 dequantization race in _convert_moe_packed_tensors (#47423) by @kaixuanliu in [#47423]
Audio
Batched audio generation is now supported for Qwen2.5/3-Omni, and several bug fixes were applied across audio models, including a dtype mismatch in Gemma4 audio feature merging, a bfloat16 positional embedding error in AudioFlamingo3, and missing backend requirement guards for Voxtral. The VibeVoice ASR processor was also updated to make audio input optional and support multiple audios per prompt.
feat[vLLM x v5]: Make audio optional and support multiple audios in VibeVoice ASR processor (#47483) by @harshaljanjani in [#47483]
Fix Gemma4 audio feature dtype mismatch in masked_scatter (#47482) by @danielhanchen in [#47482]
[fix] fix requirements audio feature and proc (#47113) by @eustlb in [#47113]
[AudioFlamingo3] Fix bfloat16 dtype mismatch in audio encoder positional embedding (#47258) by @snkii in [#47258]
Parallelization
Expanded FSDP support across 94 ForCausalLM model classes with auto-generated FSDP plans, added end-to-end FSDP tests including distributed checkpoint save/load and generation, and introduced a dedicated FSDP CI job. Additionally, fixed a device mismatch bug in create_bidirectional_sliding_window_mask under model parallelism and resolved a tensor parallel inference issue for models with tied embeddings.
skip fsdp tests when backend is mps (#47601) by @3outeille in [#47601]
Fix model parallel device mismatch in create_bidirectional_sliding_window_mask (#47560) by @abcgco in [#47560]
Add FSDP plans to all models (#47165) by @3outeille in [#47165]
Fix TP inference for tied embedding (#47503) by @3outeille in [#47503]
Add FSDP CI and end-to-end FSDP tests + save fsdp (#47357) by @3outeille in [#47357]
Tokenization
This release adds native support for Mistral's "tekken" tokenizer format via AutoTokenizer, fixes a CodeLlama tokenizer bug where leading whitespace was incorrectly dropped during decode, and patches a potential ReDoS vulnerability caused by unescaped tokenizer filenames being used as regex patterns in from_pretrained.
[Mistral] Add native tekken tokenizer support to AutoTokenizer (#47507) by @juliendenize in [#47507]
Fix CodeLlama tokenizer dropping leading whitespace on decode (#47488) by @SuryanshSS1011 in [#47488]
Fix potential ReDoS by escaping tokenizer filename used as regex pattern (#47498) by @hameedibrh in [#47498]
Serve
Improved the serve chat parsing to unify streaming and non-streaming paths under a single response parser that handles tool calls, reasoning, and content, simplifying the addition of new model support. Additionally, hardened daily CI reporting by fixing GitHub API diagnostic output being captured in Slack payloads and adding rate-limit resilience to prevent report failures when paginating large job matrices.
CI: Log GitHub API diagnostics to stderr (#47635) by @tarekziade in [#47635]
Update serve chat parsing (#46267) by @SunMarc in [#46267]
ci: harden daily CI reporting against GitHub API rate limits (#47382) by @tarekziade in [#47382]
Bugfixes and improvements
Fix cached_files silently returning stale file on read-only filesystem (EROFS) (#47852) by @ydshieh in [#47852]
Fix PhimoeIntegrationTest (#46539) by @ydshieh in [#46539]
make examples under doc device agnostic (#47812) by @kaixuanliu in [#47812]
cancel deterministic for XPU in gemma4 tests (#47790) by @kaixuanliu in [#47790]
Serialize post-mlinter-review after post-link to avoid PR description race (#47832) by @ydshieh in [#47832]
Use content hash for mlinter review deduplication (#47830) by @ydshieh in [#47830]
Add new args in auto-docstring (#47737) by @zucchini-nlp in [#47737]
Add check_model_inits.py (#47656) by @guarin in [#47656]
add xpu in installation guide (#47785) by @sywangyi in [#47785]
Fix mlinter review job: checkout before artifact download (#47820) by @ydshieh in [#47820]
Post mlinter findings as inline PR review comments (#47819) by @ydshieh in [#47819]
Fix ci style (#47818) by @vasqu in [#47818]
Hotfix axk2 indexer norm (#47810) by @kmswin1 in [#47810]
open fla support for XPU to benefit from the acceleration (#47799) by @kaixuanliu in [#47799]
[docs] Update BatchEncoding.to() type annotation and docstring (#47789) by @samyuktahegde in [#47789]
Fix linting (#47807) by @Cyrilvallez in [#47807]
Fix patching in some models (#47798) by @zucchini-nlp in [#47798]
Add post-mlinter-review job to post-dashboard-link workflow (#47800) by @ydshieh in [#47800]
Migrate torchao integration off deleted torchao.dtypes (#47797) by @vkuzo in [#47797]
[conftest] Also wrap snapshot_download for EROFS fallback (#47796) by @ydshieh in [#47796]
Fix MI355 CI: bump hf-workflows pin to NUM_SLICES=4 (#47792) by @Abdennacer-Badaoui in [#47792]
[Fix] Wrong type hint in get_number_of_image_patches (#47788) by @remi-or in [#47788]
Fix Dac offload tests (#47775) by @guarin in [#47775]
[Fix] Swapped height and width in KimiK25 (#47786) by @remi-or in [#47786]
Remove dangling files and folders (#47764) by @Cyrilvallez in [#47764]
Fix AI-written conversion mappings (#47755) by @Cyrilvallez in [#47755]
update mistral common version for PR 47507 (#47677) by @itazap in [#47677]
Fix spelling/grammar in model files (batch 3/3) (#47684) by @Rocketknight1 in [#47684]
Fix spelling/grammar in core library, examples, and utils (#47685) by @Rocketknight1 in [#47685]
Fix spelling/grammar in model files (batch 2/3) (#47683) by @Rocketknight1 in [#47683]
update sonicmoe versions (#47769) by @IlyasMoutawwakil in [#47769]
clean up reverse_op fixme in compressed_tensors (#47701) by @DhanushPillay in [#47701]
PR CI with torch 2.13 (#47767) by @ydshieh in [#47767]
Import utils compilation fixes (#47726) by @IlyasMoutawwakil in [#47726]
Fix DBRX MoE hidden size and expert GLU transposes (#47671) by @kaixuanliu in [#47671]
Fix multi token decode merging (#47762) by @IlyasMoutawwakil in [#47762]
Fix: Remove redundant @can_return_tuple conflicting with @capture_out… (#47733) by @guarin in [#47733]
fix processor config nested key fallback (#47628) by @YunzhuLu in [#47628]
[CI - Debug] Skip /transformers-dependent steps for CPU runner (#47759) by @ydshieh in [#47759]
[CI] Add CPU runner support to ssh-runner workflow (#47757) by @ydshieh in [#47757]
Simplify reverse weight conversion (#47725) by @Cyrilvallez in [#47725]
Remove useless linting for inv_freq (#47753) by @Cyrilvallez in [#47753]
Use explicit nn.Buffer everywhere for modular (#47722) by @Cyrilvallez in [#47722]
Remove stale and redundant _no_split_modules entries (#47645) by @guarin in [#47645]
Executorch exporter fixes (#47243) by @IlyasMoutawwakil in [#47243]
Acc fix in xpu (#47500) by @sywangyi in [#47500]
update Dockerfile for xpu torch2.13 (#47502) by @sywangyi in [#47502]
feat[vLLM]: Support text replacement offsets in the remaining old-format processors (#47614) by @harshaljanjani in [#47614]
Fix ImportError in transformers.exporters on torch < 2.8 (#47711) by @Neal006 in [#47711]
Fix failing tests for axk1 and axk2 (#47727) by @kaixuanliu in [#47727]
Fix failing tests for granite_swa and granitemoe_swa (#47723) by @kaixuanliu in [#47723]
skip invalid test cases for inkling tests (#47493) by @kaixuanliu in [#47493]
[docs] Fix BatchEncoding documentation inconsistencies (#47647) by @samyuktahegde in [#47647]
Fix spelling/grammar in model files (batch 1/3) (#47682) by @Rocketknight1 in [#47682]
Fix spelling/grammar in English docs (q → z) (#47681) by @Rocketknight1 in [#47681]
Fix spelling/grammar in English docs (h → p) (#47680) by @Rocketknight1 in [#47680]
Fix spelling/grammar in English docs (a → g) (#47679) by @Rocketknight1 in [#47679]
fix npu check (#47587) by @DhanushPillay in [#47587]
fix: correct text input validation logic in 8 multimodal processors (and → or) (#47663) by @AbdullahRasheed45 in [#47663]
Fix feature dtype mismatch in masked_scatter for seven multimodal models (#47673) by @ in [#47673]
[docs] storing and loading chat templates (#47650) by @stevhliu in [#47650]
adding amd quark config class changes (#47322) by @debasisdwivedy in [#47322]
Fix compressed tensors impl (#47652) by @SunMarc in [#47652]
Hoist special-token lookups in wav2vec2 decode paths and drop a dead filter in wav2vec2_phoneme (#47557) by @ishan-1010 in [#47557]
silencing elastic warning by import distributed lib inside functions (#47665) by @3outeille in [#47665]
Fix missing github_utils.py download in PR CI dashboard workflow (#47668) by @ydshieh in [#47668]
Exportable kimi (#47096) by @IlyasMoutawwakil in [#47096]
better guarding to handle torch compiled with USE_DISTRIBUTED=0 (#47619) by @3outeille in [#47619]
Remove gemma4 warnings (#47664) by @Cyrilvallez in [#47664]
[Chat Parsing] Type inline tool-call arguments from the calling tool's JSON Schema (#47529) by @yonigozlan in [#47529]
Improve Trainer DataLoader Controls for Streaming and Multiprocessing (#47164) by @muyihao in [#47164]
Update maintainer list (#47644) by @Rocketknight1 in [#47644]
Allow position_ids_start=2 on DataCollatorWithFlattening for RoBERTa etc. (#47525) by @tomaarsen in [#47525]
Remove Rotary warning (#47642) by @Cyrilvallez in [#47642]
Drop multimodal inputs natively in prepare_inputs_for_generation if not in prefill (#47622) by @Cyrilvallez in [#47622]
Simplify all Rotary modules (#47598) by @Cyrilvallez in [#47598]
[docs] response_template when serving (#47626) by @stevhliu in [#47626]
[docs] MTP support (#47301) by @stevhliu in [#47301]
Fix GPT-2 c_proj depth scaling initialization (#47459) by @DavidJohnQuinlan in [#47459]
Fix fp8_linear compilability (#47623) by @IlyasMoutawwakil in [#47623]
byebye torch 2.4 (#47609) by @ydshieh in [#47609]
Vectorize NoRepeatNGramLogitsProcessor and remove its host sync (#47571) by @hameedibrh in [#47571]
Fix CUDA Graph breaking host to device copy from scalar tensor allocation (#47547) by @hmellor in [#47547]
Fix some processors (#47608) by @zucchini-nlp in [#47608]
CI: Add serge review relay workflow and review rules (#47610) by @tarekziade in [#47610]
[docs] Exporters (#47374) by @stevhliu in [#47374]
CI: use a single function for GH calls (#47474) by @tarekziade in [#47474]
Remove redundant guarding for distributed (#47570) by @3outeille in [#47570]
Fix modular for mamba packages (#47494) by @Cyrilvallez in [#47494]
Remove deprecated conversion in Kimi (#47581) by @zucchini-nlp in [#47581]
CI: use transformers-ci daily workflow with OTEL (#47360) by @tarekziade in [#47360]
Fix slow tensor path in _check_special_mm_tokens (#47580) by @guan404ming in [#47580]
CI: let's run integration failure cron at 10pm (#47537) by @tarekziade in [#47537]
Better and more extensive tests for RoPE (#46912) by @zucchini-nlp in [#46912]
Fix mamba2 family decode and simplify all reshape ops (#47569) by @Cyrilvallez in [#47569]
[DiffusionGemma] Cast the decoder padding mask to bool (#47295) by @kashif in [#47295]
General maintenance (#47517) by @zucchini-nlp in [#47517]
fixed the benchmark script with DistributedConfig (#47568) by @tarekziade in [#47568]
Fix failing tests for mimo_v2_flash (#47284) by @kaixuanliu in [#47284]
Make tokenization_mistral_common importable without mistral_common installed (#47397) by @juliendenize in [#47397]
Use --flake-runs=1 in check_bad_commit.py for PR comment CI (#47522) by @ydshieh in [#47522]
Deprecate the old response_schema (#47320) by @Rocketknight1 in [#47320]
fix: add pickle support to _LazyConfigMapping for spawn multiprocessing (#46026) by @kfojcik-intel in [#46026]
Delete old deprecations (#47518) by @zucchini-nlp in [#47518]
Run only @slow tests in PR comment CI (#47521) by @ydshieh in [#47521]
Fix incorrect type hint (#47519) by @hmellor in [#47519]
Deprecate CB config in gen configuration (#47291) by @remi-or in [#47291]
[Offloading] [Bugfix] Fix fully offloaded model saving (#47336) by @kylesayrs in [#47336]
CI: fix torchaudio pinning +proper break in rnnt (#47422) by @tarekziade in [#47422]
Fix Qwen2.5-Omni Token2Wav DiT rotary embedding layout (interleaved cos/sin) (#47403) by @HenryVarro666 in [#47403]
CI: add reproduce mode to serge verify caller (#47492) by @tarekziade in [#47492]
[fix][whisper]: fix max_new_tokens handling (#46795) by @eustlb in [#46795]
Isolate MLA KV expansion to make it easier to bypass (#47460) by @hmellor in [#47460]
Fix loss alignment and Trainer token counting for encoder decoder models (#46903) by @OmkumarSolanki in [#46903]
Fix the HunyuanVL's torchvision backend (#47499) by @Mi-Jiazhi in [#47499]
[DiffusionGemma] Support gradient checkpointing (#46572) by @kashif in [#46572]
Fix failing tests for zaya (#47268) by @kaixuanliu in [#47268]
tipsv2_dpt: fix failing tests for XPU (#47292) by @kaixuanliu in [#47292]
Fix some failed test cases related with XPU Expectations (#47173) by @kaixuanliu in [#47173]
fix: guard DTensor import in sharding_utils.py for PyTorch < 2.5 (#47481) by @ in [#47481]
CPU can incur a slow path on non-contiguous magnitudes (#47351) by @vbayanag in [#47351]
Route chat management calls to the service root (#47138) (#47303) by @dhruv7477 in [#47303]
fix: liger unnecessarily materializes logits in VRAM during eval, causing OOM (#45273) by @excepshenal in [#45273]
Fix gradient inflation when combining label smoothing with gradient accumulation (#47261) by @Incheonkirin in [#47261]
Fix MoE expert decompression for non-32-divisible bit widths (#47315) by @KKothuri in [#47315]
[Qwen3ASR] Add hotword parsing, and fix language parsing and training. (#47111) by @ebezzam in [#47111]
Remove deprecated training args and is_fast property (#46917) by @cyyever in [#46917]
Consistent output shape from get_image_features (#46405) by @zucchini-nlp in [#46405]
fix failed test cases for qwen3_omni_moe model (#47449) by @kaixuanliu in [#47449]
Fix double-shifted training loss in GitForCausalLM (#47395) by @ in [#47395]
Fix CohereASR training-loss double-shift (same as Moonshine fix #46784) (#46895) by @sharmax-vikas in [#46895]
Warn when group_by_length is silently ignored for iterable datasets (#47379) by @qgallouedec in [#47379]
Update bug report list (#46607) by @molbap in [#46607]
fix: remove unreachable return in special token builder (#47420) by @hai1222 in [#47420]
Add Harry to slow CI (#47454) by @vasqu in [#47454]
BLT: vectorize patch length processing (#47385) by @sj0618 in [#47385]
Fix TrackioCallback fails to log evaluation metrics after training ends (#46935) by @lewtun in [#46935]
[Kimi] add integration tests (#47383) by @zucchini-nlp in [#47383]
Add distributed runtime utils and DistributedMixin (#47352) by @3outeille in [#47352]
Fix Cosmos 3 Edge Patch packing order (#47399) by @atharvajoshi10 in [#47399]
Fix yarn mscale_all_dim for DeepSeek v2 and Mistral 4 (#47435) by @hmellor in [#47435]
Hoist special-token lookups out of per-token loops in six slow tokenizers (#47425) by @ishan-1010 in [#47425]
fix typos and variable naming in quicktour.md (#47418) by @yashasvi-srivastava21 in [#47418]
Normalize multimodal input keys in AnyToAnyPipeline (#47074) by @Sunt-ing in [#47074]
Fix Aria checkpoint key conversion mapping (#47151) by @sywangyi in [#47151]
extend tests/models/qwen3_next/test_modeling_qwen3_next.py::Qwen3Next… (#47184) by @sywangyi in [#47184]
CI: add serge verify (GPU) caller workflow (#47381) by @tarekziade in [#47381]
Fix orthogonal_ init for low-precision dtypes (bf16/fp16) (#47252) by @janbernloehr in [#47252]
[docs] Fix decode examples and expected output in fast_tokenizers (#47369) by @samyuktahegde in [#47369]
[serge] Fix 20 integration tests for model whisper failing with output_mismatch (list output differs (10), other (6) (#47150) by @sergereview[bot] in [#47150]
[Mistral] Move MistralConverter into integrations/mistral/ package (#46603) by @juliendenize in [#46603]
Fix GLM video frame padding for temporal patches (#47141) by @labAxiaoming in [#47141]
[docs] Inkling (#47350) by @stevhliu in [#47350]
Fix Daily CI reporting issues (#47364) by @tarekziade in [#47364]
[peft] Support key_mapping with PEFT models (#46766) by @tomaarsen in [#46766]
Fix model tests for tipsv2 (#47356) by @kaixuanliu in [#47356]
Fix TimesFM 2.5 window_size AttributeError (#47363) by @kashif in [#47363]
fix: allow num_labels property to return None when id2label is unset (#47069) by @SebTardif in [#47069]
[Tests] Fix slow video tensor creation from list of numpy arrays in SmolVLM (#44731) by @Defalt-Meh in [#44731]
Update dev version on main (#47366) by @vasqu in [#47366]
Fix deepgemm on multiple devices (#47323) by @IlyasMoutawwakil in [#47323]
ci: Handle empty GitHub token in CI run lookup (#47362) by @tarekziade in [#47362]
Fix inkling feature extractor (#47349) by @ArthurZucker in [#47349]
Significant community contributions
The following contributors have made significant changes to the library over the last release:
@ydshieh
Fix cached_files silently returning stale file on read-only filesystem (EROFS) (#47852)
Fix PhimoeIntegrationTest (#46539)
Serialize post-mlinter-review after post-link to avoid PR description race (#47832)
Use content hash for mlinter review deduplication (#47830)
Fix mlinter review job: checkout before artifact download (#47820)
Post mlinter findings as inline PR review comments (#47819)
Add post-mlinter-review job to post-dashboard-link workflow (#47800)
[conftest] Also wrap snapshot_download for EROFS fallback (#47796)
[conftest] Fix EROFS fallback for kernel downloads (correct interception point) (#47794)
[conftest] Fix EROFS fallback for kernel downloads via HfApi (#47791)
PR CI with torch 2.13 (#47767)
[CI - Debug] Skip /transformers-dependent steps for CPU runner (#47759)
[CI] Add CPU runner support to ssh-runner workflow (#47757)
Update daily CI Docker image to torch 2.13.0 / CUDA 13.0 (#47738)
Fix missing github_utils.py download in PR CI dashboard workflow (#47668)
byebye torch 2.4 (#47609)
Use --flake-runs=1 in check_bad_commit.py for PR comment CI (#47522)
Run only @slow tests in PR comment CI (#47521)
@kaixuanliu
make examples under doc device agnostic (#47812)
cancel deterministic for XPU in gemma4 tests (#47790)
open fla support for XPU to benefit from the acceleration (#47799)
Fix DBRX MoE hidden size and expert GLU transposes (#47671)
Fix failing tests for axk1 and axk2 (#47727)
Fix failing tests for granite_swa and granitemoe_swa (#47723)
skip invalid test cases for inkling tests (#47493)
Fix failing tests for mimo_v2_flash (#47284)
Fix failing tests for zaya (#47268)
tipsv2_dpt: fix failing tests for XPU (#47292)
Fix some failed test cases related with XPU Expectations (#47173)
add paged attention tests support for XPU (#47163)
Fix multi-device mxfp4 dequantization race in _convert_moe_packed_tensors (#47423)
fix failed test cases for qwen3_omni_moe model (#47449)
Fix model tests for tipsv2 (#47356)
@vasqu
Fix ci style (#47818)
🚨 [Kernels] Refactor all linear attn models & native kernels fallback (#47630)
[Kernels] Refactor function handling (#46883)
Add AXK2 from SKT (#47528)
Add Harry to slow CI (#47454)
Update dev version on main (#47366)
[FP8] Bump kernels version (#47344)
@kmswin1
Hotfix axk2 indexer norm (#47810)
Fix A.X-K2 fp8 modules_to_not_convert normalization for the gated-norm MLP (#47578)
add_axk1 (#46867)
@remi-or
[Fix] Fix multi-head latent attention (MLA) (#47761)
[Fix] Wrong type hint in get_number_of_image_patches (#47788)
[Fix] Swapped height and width in KimiK25 (#47786)
Deprecate CB config in gen configuration (#47291)
[CB] Automatically switch attention implementation to flash (#47330)
@juliendenize
[Mistral] Add native tekken tokenizer support to AutoTokenizer (#47507)
Make tokenization_mistral_common importable without mistral_common installed (#47397)
[Mistral] Move MistralConverter into integrations/mistral/ package (#46603)
@IMvision12
Add support for batched Qwen2.5/3-Omni audio generation (#47186)
Fix Hunyuan-VL PIL image resize parity with reference preprocessing (#47233)
@jiqing-feng
🚨 Enable SDPA (and other attention backends) for T5 and propagate to the T5 family (#47014)
Fix shape mismatch in KyutaiSpeechToText generate() last window (#46952)
Fix typo in MusicgenForCausalLM.generate() (#46974)
Fix BlockMask crash in CTRL flex-attention generation (#46854)
@tarekziade
CI: Log GitHub API diagnostics to stderr (#47635)
CI: Add serge review relay workflow and review rules (#47610)
CI: use a single function for GH calls (#47474)
CI: use transformers-ci daily workflow with OTEL (#47360)
CI: let's run integration failure cron at 10pm (#47537)
fixed the benchmark script with DistributedConfig (#47568)
CI: fix torchaudio pinning +proper break in rnnt (#47422)
CI: add reproduce mode to serge verify caller (#47492)
CI: add serge verify (GPU) caller workflow (#47381)
ci: harden daily CI reporting against GitHub API rate limits (#47382)
Fix Daily CI reporting issues (#47364)
ci: Handle empty GitHub token in CI run lookup (#47362)
@daviswer
Add Granite-swa and Granitemoe-swa model support (#47179)
@ShareLer
Optimize flash attention max seqlen computation in vision attention (#47170)
@atharvajoshi10
Fix Cosmos 3 Edge Patch packing order (#47399)
Add Cosmos3 Edge model support (#47181)
Original source All of your release notes in one feed
Join Releasebot and get updates from Hugging Face and hundreds of other software products.
- Aug 3, 2026
- Date parsed from source:Aug 3, 2026
- First seen by Releasebot:Aug 4, 2026
Aug 3, 26
Hugging Face adds label filtering to Jobs with clickable chips, key=value search, and support for user and organization pages.
You can now filter your Jobs by label. Your most-used labels appear as clickable chips with job counts above the list, and a free-form key=value input lets you filter by any label, including ones not shown as chips. This works on both user and organization jobs pages. Learn more about HF Jobs: https://huggingface.co/docs/hub/jobs
Original source - Jul 22, 2026
- Date parsed from source:Jul 22, 2026
- First seen by Releasebot:Jul 22, 2026
Jul 22, 26
Hugging Face updates its MCP Server with a new hf_fs tool for simpler Hub access across repositories, storage, docs, and papers. It also adds Sandboxes for secure execution environments attached to buckets and repositories, enabling faster code access for analysis, training, and Space creation.
The Hugging Face MCP Server has been updated to provide enhanced connectivity to the Hub with fewer tools and tokens.
The main change is the new hf_fs tool which provides a single interface to repositories, storage, documentation, papers and more. It's equipped with search and lets your assistant naturally navigate Hugging Face in just over 1,000 tokens.
Add Sandboxes to give your assistant secure execution environments attached to buckets and repositories. This gives blazing fast code access for dataset analysis, model training, Space creation and much more.
Share your feedback on MCP here and update your settings at https://huggingface.co/settings/mcp
Original source - Jul 21, 2026
- Date parsed from source:Jul 21, 2026
- First seen by Releasebot:Jul 21, 2026
Jul 21, 26
Hugging Face adds dashboard egress tracking with per-user breakdowns for organizations.
Users can now see their egress usage directly in the dashboard.
Organizations also receive a per‑user egress breakdown, showing how much data each member consumes.
The view currently includes only traffic routed through the Hugging Face CDN, and coverage will expand as more traffic is directed through the CDN.
Original source Similar to Hugging Face with recent updates:
- xAI release notes212 release notes · Latest Aug 14, 2026
- Perplexity release notes29 release notes · Latest Jul 27, 2026
- Microsoft release notes782 release notes · Latest Aug 13, 2026
- Google release notes1872 release notes · Latest Aug 13, 2026
- Notion release notes167 release notes · Latest Aug 14, 2026
- Anthropic release notes759 release notes · Latest Aug 15, 2026
- Jul 16, 2026
- Date parsed from source:Jul 16, 2026
- First seen by Releasebot:Jul 16, 2026
Patch release: v5.14.1
transformers releases a patch update that fixes several Inkling integration issues, including assisted generation with EncoderDecoderCache and prefill problems with StaticCache and sdpa, while also updating FP8 kernels and deepgemm support.
Patch release v5.14.1
This patch solves a few issues which appeared when integrating Inkling model, most notably an issue affecting models using EncoderDecoderCache during assisted generation. It also fixes an issue that could appear during prefill with StaticCache and sdpa without padding for Inkling which uses a position_bias.
It contains the following commits:
- Fix sdpa prefill with position_bias (#47359) by @Cyrilvallez
- Fix assisted decoding for models with EncoderDecoder cache & OlmoHybrid (#47361) by @Cyrilvallez
- [FP8] Bump kernels version (#47344) by @vasqu
- Fix deepgemm on multiple devices (#47323) by @IlyasMoutawwakil
- Jul 16, 2026
- Date parsed from source:Jul 16, 2026
- First seen by Releasebot:Jul 16, 2026
- Modified by Releasebot:Jul 22, 2026
Jul 16, 26
Hugging Face adds AI agent creation for new Spaces, letting users generate commands to build and iterate on projects.
The new Space creation page now includes an option to build with an AI agent. Copy the generated command into your agent and let it build and iterate on a Space for a model, paper, or local folder.
https://huggingface.co/new-space
Original source - Jul 15, 2026
- Date parsed from source:Jul 15, 2026
- First seen by Releasebot:Jul 15, 2026
Release v5.14.0
transformers releases v5.14.0 with new model additions like Inkling and TIPSv2, plus major generation, cache, kernel and performance improvements. It also brings breaking backend updates for GPTNeoX and GPTBigCode, alongside many fixes and compatibility upgrades.
Release v5.14.0
New Model additions
Inkling (fresh from Thinking Machines): 975B total, 41B active
Add Inkling model #47347 by @molbap @Cyrilvallez @eustlb and @zucchini-nlp
Inkling is a general-purpose multimodal model that accepts text, image and audio inputs and generates text outputs. It is intended for use in English and other languages, and across multiple coding languages. The model is designed to be used by developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation systems, and is suitable for general-purpose conversational use, instruction-following, and other natural language and multimodal tasks. It is released with open weights to support research, fine-tuning and integration into third-party products by downstream developers.
TIPSv2
Links: Documentation
Add TIPSv2 (#46347) by @Ternura143 in #46347
TIPSv2 DPT
Links: Documentation
Add TIPSv2 (#46347) by @Ternura143 in #46347
🚨 Breaking changes
GPTNeoX now remaps embed_out to lm_head and GPTBigCode has _supports_attention_backend = True enabled for vLLM compatibility; users relying on the previous weight naming or attention backend behavior for these models should update their code accordingly.
🚨 Fix GPTBigCode and GPTNeoX for the Transformers modelling backend for vLLM (#47198) by @hmellor
Kernels
Several kernel-related fixes and improvements were made, including pinning the kernels dependency to a compatible version in the benchmark workflow, removing a deprecated package_name argument from LocalLayerRepository, and making the DeepGEMM Triton fallback more robust when CUDA_HOME is unset or misconfigured. Additionally, SDPA prefill was updated to leverage the FlashAttention kernel with StaticCache, yielding significant performance gains (up to 260% faster for large input sizes).
Pin kernels to compatible version in benchmark workflow (#47339) by @tarekziade in [#47339]
[Fix] Remove deprecated argument from kernels call (#47100) by @remi-or in [#47100]
[Fix] Make DeepGEMM triton fallback more robust (#47126) by @remi-or in [#47126]
[sdpa] Allow prefill to use FA kernel with StaticCache (#47094) by @Cyrilvallez in [#47094]
Generation
Generation improvements include adding Multi-Token Prediction (MTP) decoding support, static ensemble verification for speculative decoding to improve draft token acceptance rates, and a fix for crashes in greedy assisted generation with different tokenizers. A misleading double-negative warning message for synced_gpus in continuous batching mode was also corrected.
[generation] Fix misleading synced_gpus warning in continuous batching (#47158) by @Partha-Shankar in [#47158]
[generate] Add proper MTP support (#46229) by @Cyrilvallez in [#46229]
Fix crash in greedy assisted generation with different tokenizers (#46936) by @Sunt-ing in [#46936]
[Generation] Add static ensemble verification for lossy speculative decoding (#45979) by @kasakh in [#45979]
Performance
Fixed a Flash Attention performance regression affecting models like Qwen3-VL and resolved a MoE decode optimization bug where the grouped-to-batched matrix multiplication switch was not applied to experts residing in submodels (e.g., VLMs with a nested text config).
Fix FA performance regression (#47134) by @andreasgoulas in [#47134]
Fix MoE decode optimization for experts living in a submodel (#47107) by @IlyasMoutawwakil in [#47107]
Make doc builds faster (#47099) by @mishig25 in [#47099]
Cache
Cache dispatch logic was simplified by introducing explicit layer-type mappings for sliding and static layers, reducing complexity in cache routing. Additionally, fixes were made for read-only cache failures in CPU CI environments and for MPS graph cache growth during variable-length batch training on Apple Silicon.
Fix CI read-only cache failures by patching cached_files in conftest (#47043) by @ydshieh in [#47043]
trainer: clear MPS graph cache via torch_empty_cache_steps (#45818) by @anagnorisis2peripeteia in [#45818]
[cache] Simplify cache dispatch based on layer_types (#47118) by @Cyrilvallez in [#47118]
Bugfixes and improvements
ci: cover xet as well (runtime error) (#47338) by @tarekziade in [#47338]
[docs] TokenizersBackend fallback (#47302) by @stevhliu in [#47302]
Resolve continuous batching XPU availability checks at runtime (#47185) by @kaixuanliu in [#47185]
[Nit] Add kernels_fallback_ok kwarg to is_flash_attn_N_available (#47318) by @remi-or in [#47318]
[Nit] Add expectations for gemma4 tests on H100 (#47311) by @remi-or in [#47311]
[docs] DeepGEMM requirements (#47324) by @stevhliu in [#47324]
DeepGEMM shouldn't pad on SM90 (#47313) by @IlyasMoutawwakil in [#47313]
Fix half-precision torch.compile crash in DETR-family sine position embeddings (#47238) by @David-Wu1119 in [#47238]
Fix hardcoded paths in siglip checkpoint/vocab loading (#47178) by @XanxusCrypto in [#47178]
Update AMD CI runner groups to amd-mi300 (#47307) by @Abdennacer-Badaoui in [#47307]
Point to Gemma 4 model in Gemma4ForCausalLM docstring example (#47255) by @lefft in [#47255]
Fix Qwen Omni batched text postprocessing (#47197) by @Sunt-ing in [#47197]
Fix AqlmConfig error messages to say "int" instead of "float" (#47089) by @Sreekant13 in [#47089]
Fix check for interactive stdout in _style function (#47283) by @smart8986 in [#47283]
Fix get_json_schema crash on non-string docstring choices (#47072) by @Sreekant13 in [#47072]
Make MODEL_IDS_TO_TOKENIZERS_BACKEND capture all DeepSeek R1 distills (#47296) by @hmellor in [#47296]
Update doc preprocessing regex to prevent ReDoS (#47187) by @WilliamRoyNelson in [#47187]
Shard on read Dtensor aware (#46717) by @3outeille in [#46717]
Switch AMD daily CI to mi300 runners (#47259) by @Abdennacer-Badaoui in [#47259]
tests: reduce processor test memory usage by using tiny Hub checkpoints (#47213) by @ydshieh in [#47213]
Torch compile backend defaults to "neuron" (#47035) by @michaelbenayoun in [#47035]
Fix flash-attn Docker build broken by setuptools 83 removing pkg_resources (#47251) by @ydshieh in [#47251]
Add heterogeneous config support (per-layer configuration) (#45333) by @eladsegal in [#45333]
[fix] update integration test values (#47146) by @eustlb in [#47146]
Fix DeepSpeed SP loss aggregation and LocalLayerRepository kwargs (#47073) by @sshivampeta in [#47073]
tests only for the top 10 download models (#47244) by @3outeille in [#47244]
Fix InputTokensDetails missing cache_write_tokens for openai>=2.34.0 (#47248) by @ydshieh in [#47248]
Revert "Trigger a scheduled run" (#47249) by @ydshieh in [#47249]
Remove Executorch from CI until latest version is supported and fully tested on CI env (#47242) by @IlyasMoutawwakil in [#47242]
Be more defensive with remap_legacy_layer_types for custom models (#47245) by @hmellor in [#47245]
Fix DistributedConfig docstring for unimplemented sp_plan (#47237) by @3outeille in [#47237]
Switch mlinter to 0.1.2 (#47172) by @tarekziade in [#47172]
Trigger a scheduled run (#47209) by @ydshieh in [#47209]
Make executorch exporter tests always use xnnpack backend (#47201) by @tarekziade in [#47201]
No agent PR descriptions (#45790) by @Rocketknight1 in [#45790]
Clarify that max_steps is required for datasets without len (#47155) by @albertvillanova in [#47155]
Cleanup pipelines, stop materializing generators (#47142) by @Rocketknight1 in [#47142]
Fix device_map computation when the no_split_modules have different sizes (#47203) by @Cyrilvallez in [#47203]
Add native FSDP2 module + migration (#46707) by @3outeille in [#46707]
Fix experts implementation in two spots (#47097) by @remi-or in [#47097]
[Fix] Remove old automatic cross attn pattern from output recorders (#47117) by @remi-or in [#47117]
🌐 [i18n-KO] Translate accelerator_selection.md to Korean (#47157) by @kkwjk2718 in [#47157]
[i18n-KO] Translate optimum.md to Korean and fix Furiosa typo (#47156) by @kkwjk2718 in [#47156]
[docs] fix curly quotes rendering to straight quotes (#47135) by @clijo in [#47135]
Fix custom code which doesn't know about the new linear layer type names (#47174) by @hmellor in [#47174]
Reject path traversal in the transformers_weights config field (#46890) by @LinZiyuu in [#46890]
[docs] Custom code conversion mapping (#47114) by @stevhliu in [#47114]
Add exporters min version requirements and test skip (#47161) by @IlyasMoutawwakil in [#47161]
tests: reduce processor test memory usage and use tiny test assets (#47168) by @ydshieh in [#47168]
Clarify input device placement in the Quicktour inference example (#47136) by @samyuktahegde in [#47136]
Extend continuous batching memory prediction test to XPU (#47159) by @sywangyi in [#47159]
Fix case where _LazyAutoMapping.register is passed a str key (#47148) by @hmellor in [#47148]
[docs] MoE decode switching (#47149) by @stevhliu in [#47149]
add XPU output expectations for minicpm3 tests (#47092) by @kaixuanliu in [#47092]
Diffusion gemma: fix failed test cases (#47025) by @kaixuanliu in [#47025]
add XPU Expectation for cosmos3_omni tests (#46880) by @kaixuanliu in [#46880]
Fix IndexError Bug in XLMRoberta/Camembert ForMultipleChoice by restoring the pooler (#47147) by @pariidanDKE in [#47147]
Skip caching_allocator_warmup on Neuron (no reuse pool to warm; currently OOMs) (#47029) by @dacorvo in [#47029]
[docs] continuous batching (offloading behavior, max batch tokens, block size minimum) (#46925) by @stevhliu in [#46925]
[docs] fix autolinks (#46968) by @stevhliu in [#46968]
revert #47121 (#47144) by @eustlb in [#47144]
Fix output labels for AudioFlamingo3 (and related) models (#47112) by @ebezzam in [#47112]
Fix false len claims in Trainer docstrings (#47131) by @albertvillanova in [#47131]
processor tests: use tiny Hub repos to reduce CI memory (#47115) by @ydshieh in [#47115]
[serge] Fix 12 integration tests for model dac failing with output_mismatch (tensor values differ (6), other (6)) (#47121) by @sergereview[bot] in [#47121]
Fix CLI compatibility with huggingface_hub 1.22 (#47059) (#47064) by @dhruv7477 in [#47064]
we want to run the CI in the release branches (#47125) by @tarekziade in [#47125]
Small improvement (#47128) by @Cyrilvallez in [#47128]
[Model] Support use_cache=False for DeepSeek V4 (#46965) by @kylesayrs in [#46965]
docs-fix: IMDb dataset link in sequence classification guide (#47062) by @abhishekkapoorx in [#47062]
Fix AltCLIP text embedding resize test (#47079) by @IMvision12 in [#47079]
fix mask return-type contract regression and add correctness guard for (#47019) by @kaixuanliu in [#47019]
Fix save_pretrained with offloading and weight conversions (#47018) by @Cyrilvallez in [#47018]
Update dev (#47044) by @vasqu in [#47044]
[Gemma4] Update 1 integration test (#47042) by @vasqu in [#47042]
Significant community contributions
The following contributors have made significant changes to the library over the last release:
@ArthurZucker
v5.14.0
@tarekziade
ci: cover xet as well (runtime error) (#47338)
Pin kernels to compatible version in benchmark workflow (#47339)
Switch mlinter to 0.1.2 (#47172)
Make executorch exporter tests always use xnnpack backend (#47201)
Remove executorch from all-latest-gpu image + add torch smoke test (#47196)
we want to run the CI in the release branches (#47125)
@remi-or
[Nit] Add kernels_fallback_ok kwarg to is_flash_attn_N_available (#47318)
[Nit] Add expectations for gemma4 tests on H100 (#47311)
[Fix] Remove deprecated argument from kernels call (#47100)
[Fix] Make DeepGEMM triton fallback more robust (#47126)
Fix experts implementation in two spots (#47097)
[Fix] Remove old automatic cross attn pattern from output recorders (#47117)
@ydshieh
tests: reduce processor test memory usage by using tiny Hub checkpoints (#47213)
Fix flash-attn Docker build broken by setuptools 83 removing pkg_resources (#47251)
Fix InputTokensDetails missing cache_write_tokens for openai>=2.34.0 (#47248)
Revert "Trigger a scheduled run" (#47249)
Fix CI read-only cache failures by patching cached_files in conftest (#47043)
Trigger a scheduled run (#47209)
tests: reduce processor test memory usage and use tiny test assets (#47168)
processor tests: use tiny Hub repos to reduce CI memory (#47115)
@eladsegal
Add heterogeneous config support (per-layer configuration) (#45333)
@eustlb
[fix] update integration test values (#47146)
revert #47121 (#47144)
@Ternura143
Add TIPSv2 (#46347)
Original source - Jul 14, 2026
- Date parsed from source:Jul 14, 2026
- First seen by Releasebot:Jul 16, 2026
Jul 14, 26
Hugging Face adds fine-grained token presets for faster, clearer access token setup and one-click organization linking.
Fine-Grained Token Presets
You can now create fine-grained access tokens from presets: Read-Only, Inference, Write, CI/CD, or Full Access. Pick a preset to get a curated set of permissions with a clear summary of what the token can do, attach organizations in one click, or switch to Custom to fine-tune individual permissions as before.
Presets are also linkable: URLs like /settings/tokens/new?preset=inference or /settings/tokens/new?preset=read-only&orgs=huggingface take you straight to a pre-configured token, handy for docs and onboarding guides.
Original source - Jul 11, 2026
- Date parsed from source:Jul 11, 2026
- First seen by Releasebot:Jul 12, 2026
Patch release v5.13.1
transformers ships a patch release focused on enabling support for the latest vLLM release and improving custom model handling.
Patch release v5.13.1
This patch is focused on enabling transformers for the latest release of vllm!
- Be more defensive with remap_legacy_layer_types for custom models (#47245) from @hmellor
- Fix custom code which doesn't know about the new linear layer type names (#47174) from @hmellor
- Fix case where _LazyAutoMapping.register is passed a str key (#47148) from @hmellor
- Jul 3, 2026
- Date parsed from source:Jul 3, 2026
- First seen by Releasebot:Jul 3, 2026
Release v5.13.0
transformers releases v5.13.0 with major new model support, broader export and kernels tooling, and a long list of generation, attention, cache, quantization, and serving fixes. It also adds unified HfExporter support for PyTorch, ONNX, and ExecuTorch, plus several breaking modeling updates.
Release v5.13.0
New Model additions
KimiK 2.5, 2.6, and 2.7
This release includes the architecture for Kimi 2.5 which is used by 2.5-2.7:
Kimi K2.5 is an open-source, native multimodal agentic model that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration. The model was proposed in Kimi K2.5: Visual Agentic Intelligence and further improved in [Kimi K2.6: Advancing Open-Source Coding](Kimi K2.5: Visual Agentic Intelligence).
Kimi K2.5 achieves significant improvements on complex, end-to-end coding tasks, generalizing robustly across programming languages (Rust, Go, Python) and domains spanning front-end, DevOps, and performance optimization. The model is capable of transforming simple prompts and visual inputs into production-ready interfaces and lightweight full-stack workflows, generating structured layouts, interactive elements, and rich animations with deliberate aesthetic precision.
Links: Documentation
Add new model: Kimi2-6 (#45630) by @zucchini-nlp in #45630
MiMo-V2-Flash
MiMo-V2-Flash is a Mixture-of-Experts (MoE) language model developed by the Xiaomi MiMo team. Designed to establish a new balance between long-context modeling capabilities and inference efficiency, the model is built for strong performance in complex reasoning and agentic tasks. Trained on 27T tokens with native 32k sequence lengths, MiMo-V2-Flash seamlessly supports an extended 256K context window while significantly reducing KV-cache storage compared to standard global attention models.
Links: Documentation
Add Xiaomi MiMo-V2 (#45144) by @casinca in #45144
Nemotron 3.5 ASR
Nemotron 3.5 ASR is a 600M-parameter multilingual speech recognition model from NVIDIA, built for high-quality transcription in both low-latency streaming and high-throughput batch settings, with native punctuation and capitalization. For streaming, it offers configurable chunk sizes—80ms, 160ms, 560ms, and 1120ms, letting users trade off latency against accuracy to suit their application. Its cache-aware FastConformer-RNNT architecture is central to this capability: unlike traditional buffered streaming, which repeatedly reprocesses overlapping audio windows, the model processes only each new incoming chunk while reusing cached encoder context from prior chunks. This eliminates redundant computation, significantly improves efficiency, and minimizes end-to-end delay without sacrificing accuracy, making it well suited to real-time transcription workloads.
Links: Documentation
Add Nemotron 3.5 ASR Streaming (#46565) by @eustlb in #46565
NemotronAsrStreaming
Nemotron ASR Streaming is a 600M-parameter English speech recognition model from NVIDIA, built for high-quality transcription in both low-latency streaming and high-throughput batch settings, with native punctuation and capitalization. For streaming, it offers configurable chunk sizes—80ms, 160ms, 560ms, and 1120ms, letting users trade off latency against accuracy to suit their application. Its cache-aware FastConformer-RNNT architecture is central to this capability: unlike traditional buffered streaming, which repeatedly reprocesses overlapping audio windows, the model processes only each new incoming chunk while reusing cached encoder context from prior chunks. This eliminates redundant computation, significantly improves efficiency, and minimizes end-to-end delay without sacrificing accuracy, making it well suited to real-time transcription workloads.
Links: Documentation
Add Nemotron ASR Streaming (#46332) by @eustlb in #46332
Qwen3 ASR
Qwen3 ASR is an automatic speech recognition model from Alibaba's Qwen team that combines a Whisper-style audio encoder with a Qwen3 language model decoder for speech-to-text transcription. The model supports automatic language detection and multilingual transcription.
A forced aligner model is also included. It can be used to timestamp a provided transcript and its audio. It uses the same audio encoder model with a classification head that predicts a word's length. This model can be used with the transcript from any ASR model (see the example below with Parakeet CTC).
Links: Documentation
Qwen3 ASR and Forced Aligner (#43838) by @mbtariq82 in #43838
ZAYA
ZAYA1 is a 760M active / 8.4B total parameter MoE language model trained by Zyphra. It combines Compressed
Convolutional Attention (CCA), a nonlinear ZAYA1 router, and residual scaling.Links: Documentation
[new model] Add Zyphra/ZAYA1-8B (#45862) by @JJJYmmm in #45862
VideoPrism
The VideoPrism model was proposed in the paper VideoPrism: A Foundational Visual Encoder for Video Understanding by Google DeepMind (blog post).
VideoPrism is a general-purpose video encoder that tackles diverse video understanding tasks with a single frozen model. The model is pretrained on a large-scale heterogeneous corpus containing 36M high-quality video-caption pairs and 582M video clips with noisy parallel text (e.g. ASR transcripts). The pretraining approach improves upon masked autoencoding through global-local distillation of semantic video embeddings and a token shuffling scheme, enabling the model to focus primarily on the video modality while leveraging text associated with videos. VideoPrism achieves state-of-the-art performance on 31 out of 33 video understanding benchmarks across four broad task groups, from web video question answering to computer vision for science.
Links: Documentation
Add Videoprism (#39895) by @MHRDYN7 in #39895
RADIO
RADIO (Reduce All Domains Into One) is a family of vision foundation models from NVIDIA trained by multi-teacher distillation (e.g. CLIP, DINOv2, SAM) into a single ViT backbone. It produces both an image-level summary embedding and dense spatial features, and supports variable input resolutions through a Cropped Position Embedding (CPE) patch generator.
Links: Documentation
Add support for RADIO models (#46425) by @meatybobby in #46425
MiniCPM3
MiniCPM3 is the third-generation MiniCPM dense language model from OpenBMB. The 4B variant
(openbmb/MiniCPM3-4B) outperforms many 7B–9B open
models on standard benchmarks while remaining lightweight enough for on-device usage.MiniCPM3 combines several architectural ideas:
Multi-head Latent Attention (MLA) from DeepSeek-V2, which compresses the key/value cache
into a low-rank latent representation while still using rotary embeddings on a portion of the
query/key heads.A standard SwiGLU MLP (no MoE).
Three scalar scaling factors that govern signal flow:
scale_emb — scales input embeddings.
scale_depth / sqrt(num_hidden_layers) — scales residual connections.
hidden_size / dim_model_base — scales hidden states before the language model head.
Links: Documentation
Add MiniCPM3 (#41116) by @bzantium in #41116
Breaking changes
A broad set of modeling changes have been made to standardize layer declarations, mask/cache construction, and hybrid-attention handling, making many models cleanly exportable (ONNX, torch.export, ExecuTorch) and fullgraph-compilable — users relying on internal modeling APIs may need to update their code accordingly.
🚨 Modeling changes for export, compile, and hybrid-attention standardization (#46738) by @IlyasMoutawwakil
Attention masking for image tokens in Gemma 3/4 models has been fixed to correctly respect sliding window boundaries in local layers, which changes model behavior and may affect reproducibility of previous results.
🚨 [gemma 3/4] Fix bidirectional attention masking crossing sliding window boundaries (#46850) by @douglas-reid
The Expert Parallelism (EP) router contract has been corrected across many models and FP8 scale format handling has been fixed, requiring users of EP or FP8 quantization with affected models to verify their configurations and potentially update conversion mappings.
🚨 EP: fix EP router contract for many models + honor FP8 scale format (#46818) by @IlyasMoutawwakil
The Kernels integration has been synced to the latest version, which includes a breaking change where model-type repositories are no longer accepted by the kernels interface — users must migrate to the updated kernel repository format as shown in the updated tests.
🚨 [Kernels] Sync to latest version (#46039) by @vasqu
HfExporters: Native, Unified export for PyTorch / ONNX / ExecuTorch
A native, in-Transformers export pipeline — one base class (HfExporter), three subclasses for the runtimes we care about, one unified API:
Exporter
Output
Runtime
DynamoExporter
ExportedProgram
Any PyTorch runtime, AOT compilation
OnnxExporter
ONNXProgram
Any ONNX runtime (ORT, TensorRT, OpenVINO, …)
ExecutorchExporter
ExecutorchProgramManager
Mobile and edge (ExecuTorch)Same call shape across all three. Dynamic shapes by default. Generation-style models split automatically into prefill + decode (+ vision/audio sub-encoders for VLMs).
from transformers import AutoModelForMaskedLM, AutoTokenizer from transformers.exporters import OnnxExporter, OnnxConfig model_id = "hf-internal-testing/tiny-random-BertForMaskedLM" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForMaskedLM.from_pretrained(model_id).eval() inputs = tokenizer(["Hello, my dog is cute"] * 2, return_tensors="pt") onnx_program = OnnxExporter().export(model, inputs, config=OnnxConfig(dynamic=True)) new_input = tokenizer("Hello, my cat is so adorable!", return_tensors="pt") torch.testing.assert_close( onnx_program.call_reference(**new_input)[0], # numpy reference onnx_program(**new_input)[0], # onnxruntime rtol=1e-4, atol=1e-4, )Swap one line for another runtime — DynamoExporter() / DynamoConfig or ExecutorchExporter() / ExecutorchConfig(backend=...).
For generative models the prefill/decode split is captured automatically:
from transformers import AutoModelForCausalLM, AutoTokenizer from transformers.exporters import OnnxExporter, OnnxConfig model_id = "hf-internal-testing/tiny-random-LlamaForCausalLM" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id).eval() inputs = tokenizer(["Hello, my dog is cute"] * 2, return_tensors="pt") artifacts = OnnxExporter().export_for_generation(model, inputs, config=OnnxConfig(dynamic=True)) # {"prefill": ONNXProgram, "decode": ONNXProgram} # For VLMs: also vision_encoder, audio_encoder, multi_modal_projector, language_model, lm_headKernels
Kernels: Fixed a silent SDPA math-kernel fallback for GQA models with head_dim > 256 (e.g., Gemma4) that caused O(S²) memory materialization, and resolved a regression where use_kernels=True failed to apply kernel mappings. Additional improvements include lazy loading of the default kernel mapping to prevent import failures with incompatible kernel versions, ROCm routing to AITER Triton kernels for AMD GPUs, GB10/SM121 Hub-kernel support for Qwen3.6 Gated DeltaNet, and expanded documentation for the kernel API.
Fix silent SDPA math-kernel fallback for GQA when key/value head_dim > 256 or differ (#46960) by @Butterfingrz in [#46960]
[docs] AITER kernels (#46871) by @stevhliu in [#46871]
Documentation for the kernel API (#46754) by @michaelbenayoun in [#46754]
update kernels-community/aiter-rope version (#46810) by @Abdennacer-Badaoui in [#46810]
Add GB10/SM121 Hub-kernel path for Qwen3.6 Gated DeltaNet (#46423) by @AzeezIsh in [#46423]
[Kernels] Trigger proper kernelization on use_kernels=True (#46755) by @vasqu in [#46755]
Lazily build the default kernel mapping to decouple kernels from normal transformers usage (#46681) by @jiqing-feng in [#46681]
Add some AITER kernel routing for ROCm (#46268) by @Abdennacer-Badaoui in [#46268]
fix: position ids does not exist in upstream rotary kernel (#46619) by @NanoCode012 in [#46619]
docs(zh): add Chinese translation of kernels.md (#46621) by @shoushinya123 in [#46621]
Generation
Several generation bugs were fixed, including Mamba2 chunked-prefill and speculative decoding for hybrid models (Zamba2, Nemotron-H, Bamba, FalconH1, GraniteMoeHybrid), beam search for Mamba models, prompt lookup decoding crashes with no EOS token, and incorrect stateful model handling for LFM2. Additional improvements include reduced unnecessary generation warnings, a fix for continuous batching output mutation, and a new option to keep input tensors on CPU during generation to avoid retracing on Neuron/TPU devices.
Fix Mamba2 chunked-prefill / speculative decoding for Zamba2, Nemotron-H, Bamba, FalconH1 and GraniteMoeHybrid (#46741) by @Sunt-ing in [#46741]
Remove some unnecessary generate warnings (#46955) by @Cyrilvallez in [#46955]
Reject assisted generation for LFM2 and LFM2-MoE (set _is_stateful) (#46937) by @Sunt-ing in [#46937]
Fix beam search for mamba models (#46819) by @Cyrilvallez in [#46819]
Fix prompt lookup decoding crash when no EOS token is configured (#46790) by @Sunt-ing in [#46790]
[Continuous Batching] Snapshot generation outputs without mutating request state (#46670) by @Incheonkirin in [#46670]
[docs] keep generation tensors on cpu (#46675) by @stevhliu in [#46675]
feat(generation): allow user to keep input tensors on cpu (#46590) by @dacorvo in [#46590]
Attention
Several attention-related bugs were fixed in this release, including silent SDPA math-kernel fallbacks for GQA with large head dimensions, broken Flash Attention with StaticCache, incorrect causal masking in Xcodec2, a cross-attention reshape regression in Blip2, and eager GQA support in Evolla. Accelerate hook handling was also corrected for models using linear attention to prevent silently wrong results during offloading.
Fix accelerate hooks for all models using linear attention (#46978) by @Cyrilvallez in [#46978]
Fix Xcodec2 attention to be non-causal. (#46963) by @ebezzam in [#46963]
Fix flash attention with StaticCache (#46914) by @Cyrilvallez in [#46914]
Fix Evolla eager attention for the GQA text decoder (#46860) by @jiqing-feng in [#46860]
[docs] metal flash attention (#46349) by @stevhliu in [#46349]
[Blip2] Fix cross attention reshape (#46695) by @vasqu in [#46695]
Cache
Cache APIs were improved by consolidating redundant getters into a cleaner get_max_length method and updating documentation accordingly. Several bug fixes were also applied, including correcting mask generation beyond sliding windows, fixing a dimension issue in cumulative length tracking, resolving device mismatches in offloaded cache for hybrid models, and fixing crashes when loading trust_remote_code models from symlinked local caches.
[docs] update cache apis (#46892) by @stevhliu in [#46892]
Rework some old cache getters/properties (#46862) by @Cyrilvallez in [#46862]
Fix expanded dim in the cache's cumulative length (#46856) by @Cyrilvallez in [#46856]
Fix mask when generating beyond sliding window (#46839) by @zucchini-nlp in [#46839]
Fix offloaded cache device mismatch on hybrid models (#46748) by @Sunt-ing in [#46748]
Fix dynamic module symlinked cache on trust_remote_code models (#46618) by @ldkhang1201 in [#46618]
Serve
Several fixes and improvements were made to the Serve functionality, including lazy imports to prevent CLI crashes when the optional serve extra is not installed, a fix for dropped attributes during serialization of subclassed Pydantic models, and added documentation for the kernel API.
fix(cli/serve): import serve handlers lazily so the CLI works without the serve extra (#46473) by @ in [#46473]
[Fix] Serve drops some attributes at serialization (#46680) by @remi-or in [#46680]
Reduce per_page from 100 to 50 in GitHub API calls to avoid server errors (#46678) by @ydshieh in [#46678]
Quantization
Fixed dtype casting bugs in Gemma4's vision and audio multimodal embedders when using BitsAndBytes quantization, where inputs were incorrectly cast to integer storage dtypes (uint8/int8) instead of the actual compute dtype. Also corrected FP8 quantization to round block scales before quantizing weights, ensuring dequantization produces correct values for ue8m0 (DeepSeek-V4 style) format.
[Gemma4] Fix dtype casting for quantized vision/audio embedders (#46933) by @sharmax-vikas in [#46933]
Fix dtype casting for quantized multimodal embedders (#46904) by @praful-srinivasan-027 in [#46904]
Round the ue8m0 FP8 scale before quantizing so dequant matches the stored inverse (#46763) by @Incheonkirin in [#46763]
Bugfixes and improvements
Update workflow callers to use transformers-ci (#47040) by @ydshieh in [#47040]
Add HunYuan VL model (#46417) by @Mi-Jiazhi in [#46417]
Add tiny_model_id support to ProcessorTesterMixin for memory-sensitive tests (#47005) by @ydshieh in [#47005]
chore(linter): add TRF018 modeling rule (#46259) by @tarekziade in [#46259]
[PoC] HF exporters (#41992) by @IlyasMoutawwakil in [#41992]
TST Skip PEFT tests if PEFT version is too low (#47027) by @BenjaminBossan in [#47027]
CI Add PEFT integration tests (#47021) by @BenjaminBossan in [#47021]
[glm-mode-dsa] Indexer uses interleaved rope (#46842) by @pcuenca in [#46842]
Use standard arg names in Mllama (#46977) by @zucchini-nlp in [#46977]
Bump min peft 0.19.1 remove weight conversion duplicate code (#46442) by @BenjaminBossan in [#46442]
Raise a loud error for missing prefix (#46980) by @Rocketknight1 in [#46980]
Fix typo in Qwen3 ASR no_split_module (#47002) by @ebezzam in [#47002]
only in the original repo (#46982) by @tarekziade in [#46982]
Fix typos in Gemma 4 Assistant documentation (#46975) by @RaunaqDavidNath in [#46975]
the CI status should be a comment (#46976) by @tarekziade in [#46976]
QwenVL model conversion (#46881) by @zucchini-nlp in [#46881]
Remove default dtype in FusedRMSNormGated modules (#46953) by @Cyrilvallez in [#46953]
FIX PEFT test changed error type (#46959) by @BenjaminBossan in [#46959]
Fix path traversal via vocab-file arguments in tokenizer_config.json (#46279) by @LinZiyuu in [#46279]
docs(conditional_detr): fix num_queries default in docstring (100 -> 300) (#46939) by @Kropiunig in [#46939]
Use common floats_list method for feature extractor tests. (#46956) by @ebezzam in [#46956]
Fix RT-DETR indexing error when num_feature_levels exceeds backbone o… (#46833) by @c1prk in [#46833]
Fix Florence2 training-loss double-shift (same pattern as Moonshine #… (#46898) by @sharmax-vikas in [#46898]
[Olmo3] different RoPE per layer type (#46911) by @zucchini-nlp in [#46911]
Use inspect.getsource instead of open() for source-reading in can_set*_implementation (#46207) by @rasmi in [#46207]
Don't pin the gated delta net norm to cuda:0 with a hardcoded device (#46817) by @Sunt-ing in [#46817]
Fix auto-mappings registration for remote code & fixes a few custom code issues (#46876) by @Cyrilvallez in [#46876]
Fix broken internal documentation links (#46945) by @sezer-muhammed in [#46945]
Insert a Grafana badge in the PR (#46774) by @tarekziade in [#46774]
[NemotronAsrStreaming] fix pipeline (#46870) by @eustlb in [#46870]
[NemotronAsrStreaming] processor without modular (#46865) by @eustlb in [#46865]
[Dia] Fix docs (#46923) by @vasqu in [#46923]
[Docs] Fix full disk offloading docs (#46905) by @kylesayrs in [#46905]
[CB] Changes to increase max_batch_tokens (#46712) by @remi-or in [#46712]
Redirect to diffusers pipe in docs for experimental features (#46875) by @zucchini-nlp in [#46875]
Install in docker (#46910) by @ydshieh in [#46910]
[CI] Use pre-computed _OLD_MODELS in test_new_models_require_torchvision_backend (#46882) by @ydshieh in [#46882]
call transformers-ci in a nightly run (#46811) by @tarekziade in [#46811]
[docs] full disk offloading (#46893) by @stevhliu in [#46893]
TST Run fast PEFT tests in normal CI (#45679) by @BenjaminBossan in [#45679]
nemotron_asr_streaming: set _supports_flex_attn to False (#46878) by @kaixuanliu in [#46878]
Add native masked MSE loss for Sapiens2ForPoseEstimation (#46764) by @Sainava in [#46764]
blip 2 fix (#46816) by @itazap in [#46816]
Use meshgrid for brevity (#46861) by @zucchini-nlp in [#46861]
Add xcodec2 model (#44178) by @ebezzam in [#44178]
Prevent auto-class from being modified for all models (#46844) by @zucchini-nlp in [#46844]
Add Spanish translation of the torch.compile page (#46852) by @delcenjo in [#46852]
docs: Update NeMo AutoModel doc examples (#46857) by @adil-a in [#46857]
[docs] distributed training (#44420) by @stevhliu in [#44420]
[docs] require trust_remote_code for custom_generate (#46677) by @stevhliu in [#46677]
add distributed config (#46705) by @3outeille in [#46705]
[Offloading] [Bugfix] Fix disk offloading of models with explicit tensor dtypes (#46849) by @kylesayrs in [#46849]
Streamable chat parsing (#45847) by @Rocketknight1 in [#45847]
Fix BitNet packed-weight unpacking dtype (F.linear dtype mismatch) (#46808) by @jiqing-feng in [#46808]
Fix typos in code (#46579) by @cyyever in [#46579]
Fix Moonshine training-loss double-shift (train against labels, not labels[..., 1:]) (#46784) by @Incheonkirin in [#46784]
[CB] Fix issues with FA read / writes (#46765) by @remi-or in [#46765]
Switch decorator order (#46853) by @Cyrilvallez in [#46853]
docs(trainer): add JIT checkpointing to trainer recipes (#46826) by @efazal in [#46826]
Import diffusion_gemma in models init (#46841) by @boringcrypto in [#46841]
[skills] help your agent get started (#45732) by @stevhliu in [#45732]
Fix use_cache with seq_len > 1 ( #46032) (#46084) by @Ramshankar07 in [#46084]
[Offloading] Support full disk offloading (#46749) by @kylesayrs in [#46749]
fix: raise ValueError for empty conversation in apply_chat_template (#46753) by @sharmax-vikas in [#46753]
Fix VideoPrismForVideoClassification returning last_hidden_state as h… (#46830) by @sharmax-vikas in [#46830]
Avoid NumPy 2.0 array copy-keyword deprecation in create_mm_token_type_ids (#46827) by @qgallouedec in [#46827]
docs: update apple silicon doc with safetensors 0.8.0 benefits (#46744) by @McPatate in [#46744]
[CB] Add FA2 to the fast path (#46729) by @vasqu in [#46729]
Fix flex_attention block mask creation when get_seq_length returns a tensor (#46802) by @jiqing-feng in [#46802]
Fix left-padding token selection in BioGptForSequenceClassification (#46782) by @Sunt-ing in [#46782]
Fix broken internal links in model documentation (#46807) by @ShamSaleem in [#46807]
DiffusionGemma: mask layout and CI (#46654) by @zucchini-nlp in [#46654]
Use cached added-token dicts in per-token decode loops (#46535) by @ishan-1010 in [#46535]
fix another flaky test (#46767) by @zucchini-nlp in [#46767]
Fix secondary rate limit when downloading artifacts in slack report (#46796) by @ydshieh in [#46796]
docs: move SmolLM3 to Text models category in _toctree.yml (#46770) by @yyouretoast in [#46770]
Fix several bugs in cache_implementation=static (#46446) by @dacorvo in [#46446]
[CI] Fix artifact download path in self-comment-ci workflow (#46769) by @ydshieh in [#46769]
fixes per head minimaxm3 (#46719) by @ArthurZucker in [#46719]
[CI] Fix some failures introduced by myself 😬 (#46751) by @vasqu in [#46751]
Fix regression in ProcessorMixin._load_tokenizer_from_pretrained for tokenizers at root (#46592) by @ in [#46592]
fix(aria): use math.ceil in get_number_of_image_patches to match actual patch count (#46732) by @arnavkewalram in [#46732]
Return logits from semantic segmentation post-process (#46163) by @guarin in [#46163]
Fall back to the for-loop grouped_mm on CPU (#46743) by @Sunt-ing in [#46743]
Kernelize refactor (#46520) by @michaelbenayoun in [#46520]
ci: add comment explaining why secrets are not inherited in security gate (#46750) by @ydshieh in [#46750]
ci: trigger PR CI on ci-* branches (#46746) by @ydshieh in [#46746]
finegrained v3 (#46742) by @IlyasMoutawwakil in [#46742]
Improve AutoImageProcessor error for unavailable backends (#46727) by @sisaman in [#46727]
skip decorators must appear after @parameterized.expand in pytest (#46737) by @rasmi in [#46737]
[RecurrentGemma] Support attn_implementation dispatch (#46320) by @YangKai0616 in [#46320]
[docs] clarify initialization module usage (#46698) by @stevhliu in [#46698]
feat: bump safetensors to 0.8.0 (#46523) by @McPatate in [#46523]
ci: disable CircleCI by replacing config with no-op (#46721) by @ydshieh in [#46721]
[CB] Fix offloading (#46587) by @remi-or in [#46587]
[Templates] Update members (#46720) by @vasqu in [#46720]
feat[vLLM x v5]: Expose max_source_positions on VibeVoiceAsrConfig (#46472) by @harshaljanjani in [#46472]
Laguna: support per-element output gating (#46690) by @joerowell in [#46690]
ci: grant pull-requests:write to the security gate caller (#46715) by @ydshieh in [#46715]
Multi-gpu loading when the whole backbone is tied (#46625) by @zucchini-nlp in [#46625]
Delete docstring if same as in auto-doc (#46284) by @zucchini-nlp in [#46284]
Update GLM-5.2 docs (#46703) by @Dovis01 in [#46703]
add conversion scripts for EUPE (#46691) by @molbap in [#46691]
[docs] compile level and batch/scheduling limits (#46676) by @stevhliu in [#46676]
[blip_2] Support attn_implementation dispatch (#46401) by @YangKai0616 in [#46401]
[CTRL] Support attn_implementation dispatch (#46073) by @YangKai0616 in [#46073]
Lfm2: also thread seq_idx through ShortConv.slow_forward (non-fast-path) (#46633) by @ChangyiYang in [#46633]
feat(pipelines): accept numpy arrays and tensors in ImageClassificationPipeline (#39607) (#46573) by @kamran-nizamani in [#46573]
Smovlm: pad videos up to max frames (#46662) by @zucchini-nlp in [#46662]
mistral common backend fix (#46667) by @itazap in [#46667]
[pr template] update (#46606) by @stevhliu in [#46606]
Fix AttributeError in auto_factory when model_class lacks config_class (#46669) by @atharv1945 in [#46669]
[CB] Slice logits inside the model (#46660) by @remi-or in [#46660]
ci: add NO_COLOR=1 to suppress ANSI color codes in CI output (#46659) by @ydshieh in [#46659]
Fix dynamic RoPE not resetting inv_freq when layer_type is None (#46624) by @Incheonkirin in [#46624]
Better processing tests (#46374) by @zucchini-nlp in [#46374]
ci: add merge_group trigger to pr-ci-caller.yml (#46668) by @ydshieh in [#46668]
skip invalid quant_cache test for nemotron_h (#46368) by @kaixuanliu in [#46368]
Revert "Disable PR CI workflow for PRs from forked repo. during the weekend" (#46652) by @ydshieh in [#46652]
[CB] Fix seqlens and use TypedDict (#46593) by @remi-or in [#46593]
Disable PR CI workflow for PRs from forked repo. during the weekend (#46609) by @ydshieh in [#46609]
Update post release (#46608) by @vasqu in [#46608]
Fix peft lower bound (#46605) by @hmellor in [#46605]
Fix docstring formatting issues causing Sphinx autodoc warnings (#46596) by @kurtmckee in [#46596]
Significant community contributions
The following contributors have made significant changes to the library over the last release:
@ydshieh
Update workflow callers to use transformers-ci (#47040)
Add tiny_model_id support to ProcessorTesterMixin for memory-sensitive tests (#47005)
Install in docker (#46910)
[CI] Use pre-computed _OLD_MODELS in test_new_models_require_torchvision_backend (#46882)
Fix secondary rate limit when downloading artifacts in slack report (#46796)
[CI] Fix artifact download path in self-comment-ci workflow (#46769)
ci: add comment explaining why secrets are not inherited in security gate (#46750)
ci: trigger PR CI on ci-* branches (#46746)
ci: disable CircleCI by replacing config with no-op (#46721)
ci: grant pull-requests:write to the security gate caller (#46715)
Reduce per_page from 100 to 50 in GitHub API calls to avoid server errors (#46678)
ci: add NO_COLOR=1 to suppress ANSI color codes in CI output (#46659)
ci: add merge_group trigger to pr-ci-caller.yml (#46668)
Revert "Disable PR CI workflow for PRs from forked repo. during the weekend" (#46652)
Disable PR CI workflow for PRs from forked repo. during the weekend (#46609)
@Mi-Jiazhi
Add HunYuan VL model (#46417)
@tarekziade
chore(linter): add TRF018 modeling rule (#46259)
only in the original repo (#46982)
the CI status should be a comment (#46976)
Insert a Grafana badge in the PR (#46774)
call transformers-ci in a nightly run (#46811)
@casinca
Add Xiaomi MiMo-V2 (#45144)
@JJJYmmm
[new model] Add Zyphra/ZAYA1-8B (#45862)
@ebezzam
Fix typo in Qwen3 ASR no_split_module (#47002)
Fix Xcodec2 attention to be non-causal. (#46963)
Use common floats_list method for feature extractor tests. (#46956)
Add xcodec2 model (#44178)
@meatybobby
Add support for RADIO models (#46425)
@douglas-reid
🚨 [gemma 3/4] Fix bidirectional attention masking crossing sliding window boundaries (#46850)
@Sunt-ing
Fix Mamba2 chunked-prefill / speculative decoding for Zamba2, Nemotron-H, Bamba, FalconH1 and GraniteMoeHybrid (#46741)
Reject assisted generation for LFM2 and LFM2-MoE (set _is_stateful) (#46937)
Don't pin the gated delta net norm to cuda:0 with a hardcoded device (#46817)
Fix prompt lookup decoding crash when no EOS token is configured (#46790)
Fix left-padding token selection in BioGptForSequenceClassification (#46782)
Fix offloaded cache device mismatch on hybrid models (#46748)
Fall back to the for-loop grouped_mm on CPU (#46743)
@eustlb
Add Nemotron 3.5 ASR Streaming (#46565)
[NemotronAsrStreaming] fix pipeline (#46870)
[NemotronAsrStreaming] processor without modular (#46865)
Add Nemotron ASR Streaming (#46332)
[fix] enable base64 str audio in load_audio (#46694)
@vasqu
[Dia] Fix docs (#46923)
[CB] Add FA2 to the fast path (#46729)
[Kernels] Trigger proper kernelization on use_kernels=True (#46755)
[CI] Fix some failures introduced by myself 😬 (#46751)
🚨 [Kernels] Sync to latest version (#46039)
[Templates] Update members (#46720)
[Blip2] Fix cross attention reshape (#46695)
Update post release (#46608)
@mbtariq82
Qwen3 ASR and Forced Aligner (#43838)
@remi-or
[CB] Changes to increase max_batch_tokens (#46712)
[CB] Fix issues with FA read / writes (#46765)
[CB] Fix offloading (#46587)
[Fix] Serve drops some attributes at serialization (#46680)
[CB] Slice logits inside the model (#46660)
[CB] Fix seqlens and use TypedDict (#46593)
@jiqing-feng
Fix BitNet packed-weight unpacking dtype (F.linear dtype mismatch) (#46808)
Fix Evolla eager attention for the GQA text decoder (#46860)
Fix flex_attention block mask creation when get_seq_length returns a tensor (#46802)
Lazily build the default kernel mapping to decouple kernels from normal transformers usage (#46681)
@bzantium
Add MiniCPM3 (#41116)
@MHRDYN7
Add Videoprism (#39895)
@YangKai0616
[RecurrentGemma] Support attn_implementation dispatch (#46320)
[blip_2] Support attn_implementation dispatch (#46401)
[CTRL] Support attn_implementation dispatch (#46073)
Original source - Jul 3, 2026
- Date parsed from source:Jul 3, 2026
- First seen by Releasebot:Jul 3, 2026
Diffusers 0.39.0: New image and video pipelines, core library improvements, and more
diffusers releases a major update with new pipelines for Cosmos 3, Ideogram 4, Krea 2, DreamLite, PRX Pixel, Motif-Video, AnyFlow, JoyAI, DiffusionGemma, and Anima. It also adds modular pipeline support, LoRA training and loading improvements, and core library updates.
New Pipelines
Cosmos 3
Cosmos 3 is NVIDIA's unified world foundation model (WFM) for Physical AI — a single omni-model built on a Mixture-of-Transformers (MoT) architecture that combines world generation, physical reasoning, and action generation, replacing the separate Predict, Reason, and Transfer models from earlier Cosmos releases. A single Cosmos3OmniTransformer runs a Qwen-style language model in parallel with a diffusion generation pathway, joined by a 3D multimodal RoPE. This release also lands video-to-video and action-conditioned generation, and a sound encoder.
PR: #13818
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/cosmos3
Thanks to @atharvajoshi10, @yzhautouskay, and @MaciejBalaNV for the contributions.
Ideogram 4
Ideogram 4 is a flow-matching text-to-image model that uses a multimodal text encoder and an asymmetric classifier-free guidance scheme: a dedicated unconditional_transformer produces the negative branch with zeroed text features, while the main transformer consumes the full packed text + image sequence. The pipeline ships with structured prompt upsampling and LoRA loading support.
PR: #13859
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/ideogram4
Thanks to @JinLiIdeogram for the contribution.
Krea 2
Krea 2 (K2) is a flow-matching text-to-image model built around a single-stream MMDiT with grouped-query attention. A Qwen3-VL text encoder provides the conditioning — hidden states from twelve decoder layers are tapped per token and fused inside the transformer by a small text-fusion stage — and images are decoded with the Qwen-Image VAE. Both the base (midtrain) and TDM (distilled, few-step) checkpoints are supported, alongside a LoRA DreamBooth trainer.
PR: #14045
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/krea2
Thanks to @EleaZhong and @Abhinay1997 for the contribution.
DreamLite
DreamLite is a text-to-image and image-editing model from ByteDance. It pairs a custom 2D U-Net (DreamLiteUNetModel) with the Qwen3-VL multimodal encoder as its prompt / image-instruction encoder, and uses an AutoencoderTiny (TAESD-style) VAE for fast latent encode/decode. A distilled DreamLiteMobilePipeline targets on-device, low-latency generation.
PR: #13815
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/dreamlite
Thanks to @Carlofkl for the contribution.
PRX Pixel
PRXPixel is a pixel-space text-to-image generation model by Photoroom. A ~7B PRXTransformer2DModel denoises raw RGB images directly — no VAE is needed. The model is conditioned on a Qwen3-VL text encoder and uses flow matching where the transformer predicts the clean image at each step (x-prediction).
PR: #13928
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/prx_pixel
Thanks to @DavidBert for the contribution.
Motif-Video
Motif-Video is a 2B parameter diffusion transformer for text-to-video and image-to-video generation. It features a three-stage architecture (12 dual-stream + 16 single-stream + 8 DDT decoder layers), Shared Cross-Attention for stable text-video alignment over long sequences, a T5Gemma2 text encoder, and rectified flow matching for velocity prediction.
PR: #13551
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/motif_video
Thanks to @waitingcheung for the contribution.
AnyFlow
AnyFlow from NVIDIA, NUS, and MIT is the first any-step video diffusion framework built on flow maps, enabling a single model (bidirectional or causal) to adapt to arbitrary inference budgets. It ships both bidirectional and FAR causal pipelines built on Wan2.1 backbones, covering text-to-video, image-to-video, and video-to-video.
PR: #13745
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/anyflow
Thanks to @Enderfga for the contribution.
JoyAI-Image-Edit
JoyAI-Image is a unified multimodal foundation model for image understanding, text-to-image generation, and instruction-guided image editing. It combines an 8B Multimodal LLM with a 16B Multimodal Diffusion Transformer (MMDiT). JoyImageEditPipeline supports general image editing as well as spatial editing capabilities including object move, object rotation, and camera control.
PR: #13444
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/joyimage_edit
Thanks to @Moran232 for the contribution.
DiffusionGemma
DiffusionGemma is a block-diffusion encoder-decoder language model. A causal encoder reads the clean prompt (and any previously generated blocks) into a KV cache, and a bidirectional decoder denoises a fixed-size "canvas" of tokens by cross-attending to that cache, committing the most confident tokens via the new BlockRefinementScheduler. The released checkpoint is google/diffusiongemma-26B-A4B-it.
PR: #13986
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/diffusion_gemma
Anima
Anima is a 2 billion parameter text-to-image model created via a collaboration between CircleStone Labs and Comfy Org. It is focused mainly on anime concepts, characters, and styles, but is also capable of generating a wide variety of other non-photorealistic content.
It reuses the CosmosTransformer3DModel with a Qwen3 text encoder, a T5-token text conditioner, and the AutoencoderKLQwenImage VAE.
PR: #13732
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/anima
Thanks to @rmatif for the contribution.
LTX-2.X IC LoRA and HDR Pipelines
New LTX2InContextPipeline (in-context LoRA) and LTX2HDRPipeline extend the LTX-2 family with in-context conditioning and HDR video generation.
PR: #13572
Docs: https://huggingface.co/docs/diffusers/main/api/pipelines/ltx2
Modular Pipeline Support
We added a modular pipeline for Stable Diffusion 3 (SD3) in #13324 (thanks to @AlanPonnachan).
We added a modular pipeline for Anima in #13732 (thanks to @rmatif).
LoRA loading is now enabled on ErnieImageModularPipeline (#13948) and Ideogram4ModularPipeline (#13980), thanks to @SamuelTallet.
Core Library
AutoRound quantization integration
safetensors support in the TorchAO backend and _dequantize for the TorchAO quantizer
BitsAndBytes quantization on MPS
AutoPipelineForText2Audio
AWS Neuron (Trainium/Inferentia) as an officially supported device with torch.compile compatibility
Bump safetensors to 0.8.0
Minimum supported torch version is now 2.6
Eliminate GPU sync overhead and CPU→GPU transfers across the LTX-2 pipeline
All commits
[CI] Update all workflows with permissions by @DN6 in #13672
[agents docs] update models.md with class attributes and attention mask by @yiyixuxu in #13665
Fix ignored generator in FlowMatchEulerDiscreteScheduler by @RobbinMarcus in #13678
[core] remove txt_seq_lens from qwen transformer. by @sayakpaul in #13674
[tests] fix lora tests involving clip. by @sayakpaul in #13675
post release 0.38.0 by @sayakpaul in #13670
Fix NameError in ZImageOmniPipeline when guidance_scale=0 by @Ricardo-M-L in #13527
Enable TorchAO int4wo quantization tests on XPU by @jiqing-feng in #13537
[CI] QOL improvement for PR size labeler by @DN6 in #13554
Fix BucketBatchSampler cache alignment in DreamBooth scripts by @azolotenkov in #13353
chore: update pr_labeler.yml by @hf-security-analysis[bot] in #13685
Address ernie-image review findings #13577 by @akshan-main in #13663
feat: Add Modular Pipeline for Stable Diffusion 3 (SD3) by @AlanPonnachan in #13324
Update attention_backends.md to update FA3 minimum support to Ampere by @sayakpaul in #13283
[CI] Bump style-bot SHA + switch to GitHub App by @paulinebm in #13690
[feat] JoyAI-JoyImage-Edit support by @Moran232 in #13444
Add LoRA support for Cosmos Predict 2.5 and fix pipeline to match official Cosmos repo by @terarachang in #13664
Eliminate GPU sync overhead and CPU→GPU transfers across LTX2 pipeline by @ViktoriiaRomanova in #13564
Gate deep imports from torch.distributed by @hlky in #13673
Bump diffusers from 0.20.1 to 0.38.0 in /examples/research_projects/realfill by @dependabot[bot] in #13692
Reduce WanAnimate TorchAO test input sizes to prevent OOM by @jiqing-feng in #13541
add SP support for flash_varlen_hub backend by @zhtmike in #13479
[ci] allow claude to open PRs for certain instructions. by @sayakpaul in #13536
[ci] remove compel. by @sayakpaul in #13715
styling fix. by @sayakpaul (direct commit on v0.39.0-release)
better usage of UV_PRERELEASE=allow by @sayakpaul in #13716
[docs] add magcache to caching api listing by @sayakpaul in #13714
[tests] refactor autoencoderkl tests by @sayakpaul in #13368
[docs] add docs for JoyAI-Image-Edit by @feice-huang in #13726
[tests] add attention backend tests. by @sayakpaul in #13174
Install transformers from main for doc and staging by @sayakpaul in #13723
Update Flax removal version by @DN6 in #13729
examples/dreambooth: fix LR scheduler step count for multi-GPU in train_dreambooth_lora_sd3.py by @Dev-X25874 in #13731
Serge reviewer by @sayakpaul in #13735
[ci] switch to a more unique name by @sayakpaul in #13738
fix autoencoder memory tests by @sayakpaul in #13734
Fix GGUF to Work Better with modules_to_not_convert / keep_in_fp32_modules by @dg845 in #13697
[tests] refactor ltx2 autoencoder tests to use latest mixins by @sayakpaul in #13739
feat: Add Motif-Video model and pipelines by @waitingcheung in #13551
Update contribution guidelines by @DN6 in #13753
[agents] add a section on tests in the ai skill and integration guides. by @sayakpaul in #13752
Add LTX-2.X IC LoRA and HDR Pipelines by @dg845 in #13572
[tests] Fix controlnet tests by @sayakpaul in #13736
[tests] fix bitsandbytes compile tests for flux. by @sayakpaul in #13750
[core] minimum torch version is 2.6 by @sayakpaul in #13725
[tests] fix lora checkpoint serialization issues by @sayakpaul in #13676
fix(randn_tensor): compare device.type, not torch.device, when suppressing MPS info log by @Ricardo-M-L in #13508
[LLADA2] Fix llada2 review #13598 by @kashif in #13698
fix lfs pointer rejection problems for hub tests by @sayakpaul in #13733
Fix training gradient underflow in quantization tests by @jiqing-feng in #13539
examples/dreambooth: fix missing weighting chunk when using prior preservation in Flux and SD3 LoRA training by @Dev-X25874 in #13743
Implement _dequantize for TorchAO quantizer by @jiqing-feng in #13538
fix device mismatch issue for HiDreamTransformerTests by @kaixuanliu in #13766
[docs] remove pipeline examples section by @stevhliu in #13771
[CI] Replace print_env step in CI with diffusers-cli env by @DN6 in #13662
update safetensors.torch._tobytes to safetensors.torch._to_ndarray by @sywangyi in #13770
[agents docs] update pipelines.md: by @yiyixuxu in #13570
fix(gguf): correct mismatched-shape error message in check_quantized_param_shape by @Ricardo-M-L in #13504
[CI] claude_review: target source PR's branch for follow-up PRs by @yiyixuxu in #13774
[WIP] chore: add utilities to check if call/forward methods are documented. by @sayakpaul in #13758
Fix OOM in WanAnimate BitsAndBytes Training Test by @jiqing-feng in #13777
ci: use uv overrides to make sure tokenizers install from <=0.23.0 under subs by @sayakpaul in #13767
[LTX 2.3] update docs by @linoytsaban in #13788
[docs] fix ace step checkpoint id. by @sayakpaul in #13787
Add AnyFlow Any-Step Video Diffusion Pipelines (Bidirectional + FAR Causal) by @Enderfga in #13745
Initialize ZImage pad tokens deterministically by @sywangyi in #13805
note: torch.zeros -> torch.empty by @sayakpaul in #13807
chore: enable Dependabot weekly GitHub Actions bumps by @hf-dependantbot-rollout[bot] in #13812
[ci] shorten serge name. by @sayakpaul in #13795
Adding Cosmos 3 to Diffusers by @atharvajoshi10 in #13818
This PR updates the Stable Diffusion IP-Adapter integration by @sywangyi in #13810
[AnyFlow] FAR: standalone causal-mask builder + torch.compile follow-up by @Enderfga in #13792
Update repo_id for FLASH_4_HUB in attention_dispatch by @WaterKnight1998 in #13822
Pin torchvision, torch, and torchaudio versions by @sayakpaul in #13757
[docs] Follow ups for consistent forward docstrings by @sayakpaul in #13779
refactor sana transformer tests by @akshan-main in #13826
Fix redundant Z-Image terminal timestep by @rootonchair in #13730
override torch stuff to prevent them from getting updated by @sayakpaul in #13831
Add Anima modular pipeline by @rmatif in #13732
[Feat] support AutoPipelineForText2Audio by @RuixiangMa in #13511
moved to a webhook by @tarekziade in #13836
refactor autoencoder tests (asymmetric_kl, ltx_video) by @akshan-main in #13845
Fix duplicate safetensors.load_file call in _onload_from_disk when st… by @gagandhakrey in #13851
Fix AttributeError in onnxruntime train_unconditional (args.report_to → args.logger) by @Ricardo-M-L in #13524
[fix] CLIPTextModel with transformers >= 5.6 and from_single_file by @asomoza in #13843
[tests] migrate group offloading tests to pytest by @sayakpaul in #13234
[tests] refactor caching tests. by @sayakpaul in #13235
Allow bucket reshuffling with DreamBooth caches by @azolotenkov in #13712
[Neuron] Add AWS Neuron (Trainium/Inferentia) as an officially supported device by @JingyaHuang in #13289
refactor autoencoder_magvit tests by @akshan-main in #13834
refactor autoencoder_hunyuan_video tests by @akshan-main in #13835
refactor autoencoder_kl_cogvideox tests by @akshan-main in #13840
refactor autoencoder tests (vq, kvae_video, oobleck, consistency_decoder, tiny, vidtok) by @akshan-main in #13849
updatge the test marigold to make it pass in xpu by @sywangyi in #13856
[CI] Fix torch_device import in AutoencoderTesterMixin by @DN6 in #13852
Add Ideogram 4 by @apolinario in #13859
Add structured prompt upsampling to Ideogram4 by @apolinario in #13860
[ci] add hook tests to our CI. by @sayakpaul in #13848
fix kvae gradient checkpointing tests by @sayakpaul (direct commit on v0.39.0-release)
Revert "fix kvae gradient checkpointing tests" by @sayakpaul (direct commit on v0.39.0-release)
[tests] fix anyflow tests by @sayakpaul in #13855
[CI] Refactor LTX Transformer Tests by @DN6 in #13254
[CI] Refactor Bria Transformer Tests by @DN6 in #13341
[CI] Refactor Chronoedit, PRX, EasyAnimate, Ovis transformer tests by @DN6 in #13347
Add Cosmos3 action generation support by @yzhautouskay in #13823
[docs] update philosophy.md (finally) by @yiyixuxu in #13808
fix kvae gradient checkpointing tests by @sayakpaul in #13865
[tests] Improve ideogram4 tests by @sayakpaul in #13862
[tests] migrate test_hooks.py to pytest by @sayakpaul in #13242
fix chronoedit tests on PRs by @sayakpaul in #13870
Fix the QwenImage Attention mask under Ulysses SP by @zhtmike in #13756
Add from_single_file support to ErnieImageTransformer2DModel by @akshan-main in #13727
switch to a webhook by @tarekziade in #13884
[chore] fix styling by @sayakpaul in #13885
[cli] report all quant backends in diffusers-cli env. by @sayakpaul in #13728
fix marigold depth failure in xpu and A100 by @sywangyi in #13886
refactor autoencoder tests (temporal decoder, cosmos, kvae, mochi) by @akshan-main in #13832
refactor controlnet_cosmos tests by @akshan-main in #13847
refactor unet_spatiotemporal tests by @akshan-main in #13891
Fix fp16 LoRA unscale crash after validation in train_dreambooth_lora.py by @HaozheZhang6 in #13895
[CI] Refactor Chroma , LongCat and HiDream Transformer Tests by @DN6 in #13345
[CI] Refactor Skyreels, Lumina, Ominigen, Mochi transformer tests by @DN6 in #13348
[CI] Refactor SD3 Transformer Test by @DN6 in #13340
refactor unet tests (3d_condition, motion, controlnetxs) by @akshan-main in #13897
refactor unet_1d tests by @akshan-main in #13898
refactor unet_2d tests by @akshan-main in #13901
[chore] log quant config to the user_agent by @sayakpaul in #13850
Integrate AutoRound into Diffusers by @xin3he in #13552
[tests] refactor UNet model tests to align with the new pattern by @sayakpaul in #13153
[tests] fix vidtok tests by @sayakpaul in #13894
quant config logging by @sayakpaul in #13906
Use device_map="auto" in single file tests to support large models on limited GPU memory by @jiqing-feng in #13816
Fix incorrect batch temporal IDs for cond_model_input in Flux2 Klein img2img training by @HaozheZhang6 in #13923
Incorporate safetensors support to TorchAO by @hlky in #13719
[Pipelines] Add DreamLite text-to-image and image-edit pipelines by @Carlofkl in #13815
[.ai] add self-review skill by @yiyixuxu in #13917
update PR template and highlight AI-agent setup for contributors by @yiyixuxu in #13913
[CI] implement a bot to remind prs to link issues if not. by @sayakpaul in #13744
Point "Coding with AI agents" links at the rendered docs site by @yiyixuxu in #13952
[tests] fix consistency decoder tests by @sayakpaul in #13905
Add tutorial translations in Chinese by @liwd190019 in #13932
Make root PHILOSOPHY.md a symlink to the docs philosophy page by @yiyixuxu in #13954
fix(flux): enable true CFG with precomputed negative embeds by @akshan-main in #13957
Enable LoRA loading on ErnieImageModularPipeline by @SamuelTallet in #13948
Fix typo in AutoModel by @neo in #13889
keep the agent symlinks by @yiyixuxu in #13968
[CI] allow running tests as PR comments through a bot by @sayakpaul in #13873
Add Cosmos3 video2video generation support by @yzhautouskay in #13896
[CI] Refactor Z Image Transformer Tests by @DN6 in #13253
fix untrusted fork secret mixing by @sayakpaul in #13970
start by @sayakpaul (direct commit on v0.39.0-release)
Revert "start" by @sayakpaul (direct commit on v0.39.0-release)
Add Sound Encoder to Cosmos3 by @MaciejBalaNV in #13911
Add PRXPixelPipeline: pixel-space PRX text-to-image pipeline by @DavidBert in #13928
[tests] port final set of model tests and others by @sayakpaul in #13974
Add Ideogram4LoraLoaderMixin (LoRA loading for Ideogram4) by @linoytsaban in #13921
Enable LoRA loading on Ideogram4ModularPipeline by @SamuelTallet in #13980
[Neuron] Enable torch.compile compatibility with Neuron device by @JingyaHuang in #13485
ci: don't remind on prs from admins, etc. by @sayakpaul in #13965
ci: use hosted runners by @tarekziade in #13987
Fix LTX2 connector token/register layout (regression from #13564) by @Boffee in #13931
Fix Ideogram4MRoPE collapsing under torch.autocast (compute rotary in float32) by @HaozheZhang6 in #13922
[Fix] Fix three final_layer LoRA conversion bugs in _convert_sd_scripts_to_ai_toolkit by @lcheng321 in #14001
Add Krea 2 (K2) text-to-image pipeline and transformer by @yiyixuxu in #14045
[.ai doc] Refine .ai attention-mask and component-mutation guidance by @yiyixuxu in #13982
Enable BitsAndBytes quantization in MPS by @LucasSte in #13915
fix(flux): tighten check_inputs validation by @akshan-main in #13955
Krea 2 LoRA DreamBooth trainer by @apolinario in #14046
Fix model cuda tests by @sayakpaul in #13975
[.ai] document single-file model layout and "don't reimplement Diffus… by @yiyixuxu in #14048
fix claude code review fix in PRs. by @sayakpaul in #14058
fix(bria_fibo): fix guidance_embeds, prompt_embeds, tensor-image and multi-image crashes by @akshan-main in #13981
[tests] implement base model output caching in model-level tests by @sayakpaul in #14059
[discrete diffusion] Add DiffusionGemma pipeline and schedulers by @kashif in #13986
Add from_single_file support for SkyReelsV2 and ChronoEdit transformers by @HaozheZhang6 in #13946
multi-GPU VAE Fix for Cosmos 3 by @atharvajoshi10 in #13924
docs: fix repeated word typo in set_timesteps docstring by @ramkumar27072006 in #13876
feat: bump safetensors to 0.8.0 by @porunov in #13971
Fix DreamLite legacy block type aliases by @ElectricGoal in #14066
Fix Kohya UNet LoRA key conversion for conv_in/conv_out/time_embedding by @dxqb in #14006
[Tests] Skip layerwise casting tests on devices without float8_e4m3fn support by @GiGiKoneti in #14073
[lora] add non-diffusers LoRA loading support for Krea 2 LoRAs by @linoytsaban in #14074
Add doc pages for the DiffusionGemma schedulers by @kashif in #14092
[chore] update to 2026 finally. by @sayakpaul in #14079
fix #14063 for Kandinsky5 pipeline load with device_map=balanced by @kaixuanliu in #14050
Complete Kohya LoRA conversion for Qwen and Z-Image by @dxqb in #14080
Ideogram4 lora training by @apolinario in #13861
ovis_image: fix guidance_scale / max_sequence_length / batched CFG / precomputed embeds + add pipeline test by @HaozheZhang6 in #13944
[docs] fix qwen tokenizer in docstrings. by @sayakpaul in #14098
Bump transformers from 4.47.0 to 5.3.0 in /examples/cogview4-control by @dependabot[bot] in #14109
Fix mutable default args in lora_base.py by @PrakshaaleJain in #14064
Fix FA3 varlen wrapper when hub kernel returns single tensor by @ in #14102
support loading pipeline from transformer style (flat) repo by @yiyixuxu in #14096
diffusers test installation package by @sayakpaul in #14078
[tests] fix test_from_save_pretrained_dtype_inference by @sayakpaul in #13872
Release: v0.39.0-release by @sayakpaul (direct commit on v0.39.0-release)
Significant community contributions
The following contributors have made significant changes to the library over the last release:
@DN6
[CI] Update all workflows with permissions (#13672)
[CI] QOL improvement for PR size labeler (#13554)
Update Flax removal version (#13729)
Update contribution guidelines (#13753)
[CI] Replace print_env step in CI with diffusers-cli env (#13662)
[CI] Fix torch_device import in AutoencoderTesterMixin (#13852)
[CI] Refactor LTX Transformer Tests (#13254)
[CI] Refactor Bria Transformer Tests (#13341)
[CI] Refactor Chronoedit, PRX, EasyAnimate, Ovis transformer tests (#13347)
[CI] Refactor Chroma , LongCat and HiDream Transformer Tests (#13345)
[CI] Refactor Skyreels, Lumina, Ominigen, Mochi transformer tests (#13348)
[CI] Refactor SD3 Transformer Test (#13340)
[CI] Refactor Z Image Transformer Tests (#13253)
@yiyixuxu
[agents docs] update models.md with class attributes and attention mask (#13665)
[agents docs] update pipelines.md: (#13570)
[CI] claude_review: target source PR's branch for follow-up PRs (#13774)
[docs] update philosophy.md (finally) (#13808)
[.ai] add self-review skill (#13917)
update PR template and highlight AI-agent setup for contributors (#13913)
Point "Coding with AI agents" links at the rendered docs site (#13952)
Make root PHILOSOPHY.md a symlink to the docs philosophy page (#13954)
keep the agent symlinks (#13968)
Add Krea 2 (K2) text-to-image pipeline and transformer (#14045)
[.ai doc] Refine .ai attention-mask and component-mutation guidance (#13982)
[.ai] document single-file model layout and "don't reimplement Diffus… (#14048)
support loading pipeline from transformer style (flat) repo (#14096)
@akshan-main
Address ernie-image review findings #13577 (#13663)
refactor sana transformer tests (#13826)
refactor autoencoder tests (asymmetric_kl, ltx_video) (#13845)
refactor autoencoder_magvit tests (#13834)
refactor autoencoder_hunyuan_video tests (#13835)
refactor autoencoder_kl_cogvideox tests (#13840)
refactor autoencoder tests (vq, kvae_video, oobleck, consistency_decoder, tiny, vidtok) (#13849)
Add from_single_file support to ErnieImageTransformer2DModel (#13727)
refactor autoencoder tests (temporal decoder, cosmos, kvae, mochi) (#13832)
refactor controlnet_cosmos tests (#13847)
refactor unet_spatiotemporal tests (#13891)
refactor unet tests (3d_condition, motion, controlnetxs) (#13897)
refactor unet_1d tests (#13898)
refactor unet_2d tests (#13901)
fix(flux): enable true CFG with precomputed negative embeds (#13957)
fix(flux): tighten check_inputs validation (#13955)
fix(bria_fibo): fix guidance_embeds, prompt_embeds, tensor-image and multi-image crashes (#13981)
@AlanPonnachan
feat: Add Modular Pipeline for Stable Diffusion 3 (SD3) (#13324)
@Moran232
[feat] JoyAI-JoyImage-Edit support (#13444)
@terarachang
Add LoRA support for Cosmos Predict 2.5 and fix pipeline to match official Cosmos repo (#13664)
@dg845
Fix GGUF to Work Better with modules_to_not_convert / keep_in_fp32_modules (#13697)
Add LTX-2.X IC LoRA and HDR Pipelines (#13572)
@waitingcheung
feat: Add Motif-Video model and pipelines (#13551)
@kashif
[LLADA2] Fix llada2 review #13598 (#13698)
[discrete diffusion] Add DiffusionGemma pipeline and schedulers (#13986)
Add doc pages for the DiffusionGemma schedulers (#14092)
@linoytsaban
[LTX 2.3] update docs (#13788)
Add Ideogram4LoraLoaderMixin (LoRA loading for Ideogram4) (#13921)
[lora] add non-diffusers LoRA loading support for Krea 2 LoRAs (#14074)
@Enderfga
Add AnyFlow Any-Step Video Diffusion Pipelines (Bidirectional + FAR Causal) (#13745)
[AnyFlow] FAR: standalone causal-mask builder + torch.compile follow-up (#13792)
@atharvajoshi10
Adding Cosmos 3 to Diffusers (#13818)
multi-GPU VAE Fix for Cosmos 3 (#13924)
@rmatif
Add Anima modular pipeline (#13732)
@JingyaHuang
[Neuron] Add AWS Neuron (Trainium/Inferentia) as an officially supported device (#13289)
[Neuron] Enable torch.compile compatibility with Neuron device (#13485)
@apolinario
Add Ideogram 4 (#13859)
Add structured prompt upsampling to Ideogram4 (#13860)
Krea 2 LoRA DreamBooth trainer (#14046)
Ideogram4 lora training (#13861)
@yzhautouskay
Add Cosmos3 action generation support (#13823)
Add Cosmos3 video2video generation support (#13896)
@xin3he
Integrate AutoRound into Diffusers (#13552)
@Carlofkl
[Pipelines] Add DreamLite text-to-image and image-edit pipelines (#13815)
@liwd190019
Add tutorial translations in Chinese (#13932)
@MaciejBalaNV
Add Sound Encoder to Cosmos3 (#13911)
@DavidBert
Add PRXPixelPipeline: pixel-space PRX text-to-image pipeline (#13928)
Original source - Jun 30, 2026
- Date parsed from source:Jun 30, 2026
- First seen by Releasebot:Jul 1, 2026
Jun 30, 26
Hugging Face adds a Hardware filter on Models to show only models that fit your GPU, CPU, or Apple Silicon chip.
A new Hardware filter on the Models page filters results to models that fit a specific GPU, CPU, or Apple Silicon chip, so you only see what will actually run on your machine. Set the hardware you want from your Hardware settings.
It stacks with the page's other filters and is shareable via URL, so a link like huggingface.co/models?apps=llama.cpp&hardware=apple-m4-max points anyone, even logged-out visitors, at the llama.cpp models that fit an Apple M4 Max.
Original source - Jun 26, 2026
- Date parsed from source:Jun 26, 2026
- First seen by Releasebot:Jun 26, 2026
Jun 26, 26
Hugging Face adds direct Hub feedback sharing from the user menu to report bugs and suggest improvements.
You can now share your feedback on the Hub directly with the Hugging Face team from the user menu.
Whether you want to report a bug, suggest a new feature, or share any other thoughts, your feedback will be carefully reviewed by the team to help shape future improvements.
Original source - Jun 19, 2026
- Date parsed from source:Jun 19, 2026
- First seen by Releasebot:Jun 19, 2026
Patch release v5.10.4
transformers ships patch release 5.10.4 with several fixes to keep vLLM in sync, including ProcessorMixin token ID handling, InternVL models, processing offsets, PEFT lower bounds, and the Mistral common backend.
Patch release v5.10.4
Update: Note that on pypi 5.10.3 doesn't exist and this this saved under 5.10.4 (so essentially a minor version skipped). Sorry about that, that's on me. Just wanted to clarify to make this less confusing!
A few fixes needed for vLLM to sync with transformers 🤗
- [fix] regression introduced by #45534 #46456 by @eustlb (#46456)
- Fix {image/video/audio}_token_ids in ProcessorMixin #46500 by @hmellor (#46500)
- Fix InternVL models #46524 by @hmellor (#46524)
- Fix the offsets in processing #46525 by @zucchini-nlp (#46525)
- Fix peft lower bound #46605 by @hmellor (#46605)
- mistral common backend fix #46667 by @itazap (#46667)
Full Changelog: v5.10.2...v5.10.3
Original source
Curated by the Releasebot team
Releasebot is an aggregator of official release notes from hundreds of software vendors and thousands of sources.
Our editorial process involves the manual review and audit of release notes procured with the help of automated systems.