Hugging Face Transformers: Release 5.17.0

# Release v5.17.0 ## New Model additions ### HYV4 <img width="1503" height="827" alt="image" src="https://github.com/user-attachments/assets/e6ed85ee-eb1d-40eb-a0d4-c649f6337ca9" /> Hy4-Preview is a 780B-parameter mixture-of-experts language model that activates 49B parameters per token. Each MoE layer holds 256 routed experts plus one always-active shared expert and routes every token to 8 of them. The context window is 1M tokens. The architecture combines four features: - **Multi-head Latent Attention (MLA)** compresses keys and values into a low-rank latent (`kv_lora_rank`) that `kv_b_proj` expands back to one key/value per query head. - **DeepSeek Sparse Attention (DSA)** selects `index_topk` keys per query with a lightweight indexer. Following [IndexShare](https://huggingface.co/papers/2603.12201), only the layers marked `"full"` in `indexer_types` run an indexer; `"shared"` layers reuse the previous full layer's selection. - **Gated MLA with learnable attention sinks**, where each head owns a sink logit that participates in the softmax and contributes no value, as in [GPT-OSS](./gpt_oss). - **Independent Hyper-Connections (iHC)** replace the plain residual path with `hc_mult` parallel residual streams that are collapsed before, and redistributed after, every sublayer. The implementation does not execute the multi-token prediction (MTP) layers. Released checkpoints keep those weights so that other runtimes can use them for speculative decoding; they are ignored at load time. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/hy_v4) * Add h4 (#48473) by @ArthurZucker in [#48473](https://github.com/huggingface/transformers/pull/48473) ### VibeVoice <img width="2140" height="1188" alt="image" src="https://github.com/user-attachments/assets/29ccea01-a855-4d4f-a6af-61bc4fc883a4" /> [VibeVoice](https://huggingface.co/papers/2508.19205) is a novel framework for synthesizing high-fidelity, long-form speech with multiple speakers by employing a next-token diffusion approach within a Large Language Model (LLM) structure. It's designed to capture the authentic conversational "vibe" and is particularly suited for generating audio content like podcasts and multi-participant audiobooks. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/vibevoice) * Implement VibeVoice (#40546) by @pengzhiliang in [#40546](https://github.com/huggingface/transformers/pull/40546) ### NeoMME NeoMME is a family of efficient 260M and 800M parameter multimodal-native multilingual foundation encoders from H Company. It processes multilingual text tokens and raw image patches in a single bidirectional Transformer encoder, without a separately pretrained vision tower or causal language model. NeoMME-Retriever is a model fine-tuned from the NeoMME backbone for visual document retrieval with joint late-interaction and dense objectives. It takes text queries and documents (text or page screenshots) and produces multi-vector embeddings for MeanMaxSim scoring (late-interaction) and mean-pooled embeddings for cosine similarity (dense). **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/neomme) * Add NeoMME and NeoMME-Retriever (#47992) by @tonywu71 in [#47992](https://github.com/huggingface/transformers/pull/47992) ### Fun-ASR-Nano Fun-ASR-Nano is an 800M-parameter end-to-end speech recognition model developed by Alibaba DAMO Academy's FunAudioLLM team. It achieves state-of-the-art performance on Chinese, English, and Japanese ASR benchmarks while being significantly smaller than comparable models. Key features are - **Chinese, English, and Japanese**, including 7 Chinese dialects and 26 regional accents - **Hotword customization** for domain-specific vocabulary - **Native punctuation** output (no separate punctuation model needed) **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/fun_asr_nano) * Add Fun-ASR-Nano model (#46180) by @LauraGPT in [#46180](https://github.com/huggingface/transformers/pull/46180) ### KimiLinear Kimi Linear is a hybrid linear attention architecture from Moonshot AI, introduced in [Kimi Linear: An Expressive, Efficient Attention Architecture](https://huggingface.co/papers/2510.26692). At its core is **Kimi Delta Attention (KDA)**, a refinement of [Gated DeltaNet](https://huggingface.co/papers/2412.06464) that gives each key channel its own forget gate, so the recurrent state decays per channel instead of per head. KDA is used in most layers; every fourth layer keeps a full-attention block that reuses DeepSeek-V3's Multi-head Latent Attention (MLA), and the feed-forward blocks are DeepSeek-V3-style MoE with a shared expert. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/kimi_linear) * Kimi linear (#48250) by @remi-or in [#48250](https://github.com/huggingface/transformers/pull/48250) ### Canary Canary-1B-v2, a fast, robust multilingual model for Automatic Speech Recognition (ASR) and Speech-to-Text Translation (AST): Canary reuses the [Fast Conformer](https://huggingface.co/papers/2305.05084) encoder from [Parakeet](./parakeet.md) (loaded through [`ParakeetEncoder`] / [`ParakeetEncoderConfig`]) and pairs it with a Transformer decoder that uses fixed sinusoidal positional embeddings, cross-attention to the encoder outputs and tied input/output embeddings. The task is selected through a decoder prompt prefix built by [`CanaryProcessor`] of the form `<|startofcontext|> <|startoftranscript|> <|emo:undefined|> <source_lang> <target_lang> <pnc|nopnc> <|noitn|> <|notimestamp|> <|nodiarize|>`, where `source_lang == target_lang` selects transcription and otherwise selects translation. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/canary) * model: Add NVIDIA Canary-1B-v2 to Transformers (#46825) by @harshaljanjani in [#46825](https://github.com/huggingface/transformers/pull/46825) ### NeuCodec The NeuCodec model was proposed in [Finite Scalar Quantization Enables Redundant and Transmission-Robust Neural Audio Compression at Low Bit-rates](https://huggingface.co/papers/2509.09550). NeuCodec is a neural audio codec extending on XCodec2. It takes advantage of the following features: - Finite Scalar Quantization (FSQ) quantisation resulting in a **single codebook**, making it ideal for downstream modeling with Speech Language Models. - Trained with CC data such that there are **no Non-Commercial data restrictions**. - At 50 tokens/sec and 16 bits per token, the overall bit-rate is **0.8kbps**. - The codec takes in 16kHz input and outputs **24kHz** using an **upsampling decoder**. - The FSQ encoding scheme allows for bit-level error resistance suitable for unreliable and noisy channels. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/neucodec) * Add support for NeuCodec (#47143) by @harryjulian in [#47143](https://github.com/huggingface/transformers/pull/47143) ## Breaking changes Vision rotary embeddings (2D/3D) have been standardized into a unified RoPE frequency computation module, so users with custom vision models relying on attention-layer-level or model-specific RoPE grid interleaving logic must migrate to the new centralized `modeling_rope_utils.py` implementation. * :rotating_light: Vision (2d/3d) rotary embeddings (#48105) by @zucchini-nlp ## Generation Generation improvements include a performance optimization that avoids unnecessary accelerator synchronization on every decode step (reducing per-step overhead), and a fix to prevent unconditional downloading of remote hub files during generation. Several correctness fixes were also applied, including enforcing auto-compile cache checks for encoder-decoder models, standardizing `past_key_values` naming in AfMoE, and resolving flaky export and integration test failures. * [`Generate`] Avoid unconditionally downloading remote hub file (#48620) by @vasqu in [#48620] * [generate] stop synchronizing the accelerator on every decode step (#47975) by @SunMarc in [#47975] * [AfMoE] Standardize past_key_values argument naming across forward and generate (#48430) by @shenhuaqingshi in [#48430] * Fix MTP generation test regex gate for escaped layer ignore keys (#48003) (#48262) by @Noxtimo in [#48262] * fix(generation): Enforce the auto-compile cache check for encoder-decoder models (#48364) by @harshaljanjani in [#48364] * [serge] Fix 4 integration tests for model `generation` failing with `output_mismatch` (list output differs (4)) (#48133) by @sergereview[bot] in [#48133] * [VibeVoice] Skip generate export tests (flaky) (#48396) by @ydshieh in [#48396] ## Cache Fixed several cache-related bugs, including a quantized cache issue in VibeVoice, incorrect rejection of non-static cache implementations in VoxtralRealtime, missing auto-compile cache checks for encoder-decoder models, and a silent failure when paged attention is called without a cache. Documentation was also updated to clarify `ContinuousBatchingConfig` usage and sliding window model limitations. * vibevoice: fix bug for quant cache (#48487) by @kaixuanliu in [#48487] * Fix VoxtralRealtime rejecting non-static cache implementations (#48082) by @jiqing-feng in [#48082] * Raise when a paged attention forward is called with no cache (#48297) by @qgallouedec in [#48297] * [docs] Pass ContinuousBatchingConfig and sliding window models (#48381) by @stevhliu in [#48381] * Retry get_daily_ci_runs on stale GitHub API cache (#48374) by @ydshieh in [#48374] ## Kernels Kernel support was improved with fixes for nested FLA kernel imports when only `fla-core` is installed, a warning when hub-kernel functions silently fall back to slower pure-PyTorch reference implementations, and the ability to register standalone functions (e.g., RoPE) in `KernelConfig` with optional non-inheritance of default mappings. Additional fixes include corrected repository paths for ESMFold2 kernels and updated documentation for `KernelConfig` customization. * Support nested FLA kernel imports for fla-core (#48221) by @DimensionSTP in [#48221] * Warn once when a hub-kernel function falls back to its reference PyTorch path (#48185) by @qgallouedec in [#48185] * [docs] Kernel updates (#48465) by @stevhliu in [#48465] * [`Kernels`] Enable functions into kernels registry and allow non inheritance (#48443) by @vasqu in [#48443] * Fix kernel commit and repo paths for ESMFold2 (#48186) by @Rocketknight1 in [#48186] ## Quantization Fixed several quantization bugs, including a quant cache issue in VibeVoice, incorrect FP8 embedding handling for Qwen models, missing FP8 tensor parallelism layer overrides, and unnecessary MXFP4 weight dequantization on XPU devices. * fix qwen4exp-fp8 ple embedding (#48368) by @JJJYmmm in [#48368] * Keep MXFP4 weights quantized on XPU when use_kernels is set (#47923) by @jiqing-feng in [#47923] * Fix missing FP8 TP layer overrides (#48343) by @changwangss in [#48343] ## Bugfixes and improvements * MRoPE continued (#48594) by @zucchini-nlp in [#48594] * [fix] Update stale expected strings in HunYuanVL integration tests (#48646) by @ydshieh in [#48646] * [Quantizaiton]support 5/6/7 bits in AutoRound (#48481) by @wenhuach21 in [#48481] * [fix] Update stale golden values and fix expected_logits shape in FlavaForPreTraining integration tests (#48639) by @ydshieh in [#48639] * Fix YOLOS device mismatch with device_map="auto" (#46886) by @swankystark in [#46886] * Honor `shift_labels` in decoder-only LLM/VLM losses (#48493) by @qgallouedec in [#48493] * [KimiLinear] Fix test_cpu_offload: set num_local_experts=4 in model tester (#48624) by @ydshieh in [#48624] * [docs] Per-layer config (#48601) by @stevhliu in [#48601] * Fix `generate_flags` parsing in `transformers chat` (#48597) by @SunMarc in [#48597] * [fix] Fix how we read package versions - triggered by torch 2.14+ (#48615) by @ydshieh in [#48615] * [Docker] Upgrade CPU torch to <=2.14.0, torchcodec to <=0.16.0 (#48614) by @ydshieh in [#48614] * Fix AttributeError in gradient_checkpointing_enable(offload=True) (#48590) by @tarekziade in [#48590] * Another day fixing CI (#48591) by @zucchini-nlp in [#48591] * esmfold2: keep `distogram_head` in fp32 as well (#48488) by @kaixuanliu in [#48488] * Add `supports_context_parallel` to `PreTrainedModel` (#48442) by @qgallouedec in [#48442] * [docs] mlinter reference (#48460) by @stevhliu in [#48460] * [docs] Add a LiteRT page under community integrations (#48540) by @john-rocky in [#48540] * [GLM 5.3 Flash] Fix NaN gradients in chunked KDA (#48455) by @imvladikon in [#48455] * [docs] Fix [[autodoc]] directives in ALBERT model documentation (#48593) by @samyuktahegde in [#48593] * [Fix] Fix A10 expectations for a test (#48454) by @remi-or in [#48454] * Add PR comment CI for AMD (MI300) (#48065) by @ydshieh in [#48065] * docs: fix docstring parameter names that do not match signatures (#48575) by @simpleqt in [#48575] * docs: remove phantom parameters from docstrings (#48576) by @simpleqt in [#48576] * extend some case to xpu as well (#48502) by @sywangyi in [#48502] * [serge] Fix 2 integration tests for model `glm4_moe` failing with `OOM` (other (2)) (#48551) by @sergereview[bot] in [#48551] * [serge] Fix 2 integration tests for model `nemotron` failing with `import_or_config` (other (2)) (#48582) by @sergereview[bot] in [#48582] * Compress the agent conventions file and document two modular pitfalls (#48586) by @tarekziade in [#48586] * Guard against a None video processor class when the backend is unavailable (#48557) by @caiotheodoro in [#48557] * [serge] Fix 2 integration tests regressed by commit 83d46aa2a2c4 (PR #47625) (#48580) by @sergereview[bot] in [#48580] * [nit] use requires_backends (#47576) by @eustlb in [#47576] * [serge] Fix 2 integration tests for model `kosmos2` failing with `import_or_config` (other (2)) (#48552) by @sergereview[bot] in [#48552] * Fix failing tests for cohere_compass (#48005) by @kaixuanliu in [#48005] * [Fix] Use dedicated helpers for DeepGEMM and SonicMoE tests (#48523) by @remi-or in [#48523] * CI: Point test fixtures at hf-internal-testing copies we already host (#48521) by @tarekziade in [#48521] * fix failed test cases for glm5_next (#48497) by @kaixuanliu in [#48497] * Pass kwargs to the Mamba2 mixer in Nemotron-H, Falcon-H1 and Mamba2 (#48490) by @kfastino in [#48490] * Retire test_multi_gpu_data_parallel_forward (#48508) by @tarekziade in [#48508] * Processing tests [part 2] (#47922) by @zucchini-nlp in [#47922] * QA: Add noisy comment checker (#48484) by @tarekziade in [#48484] * Allow nested rope params for tiny models (#48435) by @zucchini-nlp in [#48435] * Fix sliding-window mask `layer_idx` in Gemma3/Gemma4 `create_masks_for_vision_model` (#48482) by @jiqing-feng in [#48482] * add xpu expectations for hunyuan_vl model tests (#48504) by @kaixuanliu in [#48504] * [`Qwen 3.5 Moe`] Fix decorators (#48436) by @vasqu in [#48436] * Infinite loop in dependency search (#48393) by @zucchini-nlp in [#48393] * [serge] Fix 2 integration tests for model `fsmt` failing with `output_mismatch` (tensor values differ (2)) (#48496) by @sergereview[bot] in [#48496] * Fix some tests by removing the deprecation cycle (#48503) by @Cyrilvallez in [#48503] * Remove deprecation (#48500) by @Cyrilvallez in [#48500] * Fix Pix2StructTextAttention init using hidden_size instead of d_kv (#47558) by @<NOT FOUND> in [#47558] * Fix pre patch release utility (#48499) by @Cyrilvallez in [#48499] * Update dev version (#48498) by @Cyrilvallez in [#48498] * Fix Inkling inputs_embeds and add more tests (#47827) by @Cyrilvallez in [#47827] * Simplify and fix qwen4 tests (#48340) by @Cyrilvallez in [#48340] * [docs] Partial checkpointing and group_by_length (#48463) by @stevhliu in [#48463] * doc: fix syntax error and typos in VibeVoice documentation (#48489) by @VimalN2005 in [#48489] * [`Qwen4 Exp`] Use partial to avoid skipping mask more easily (#48456) by @vasqu in [#48456] * Add support for NeuCodec (#47143) by @harryjulian in [#47143] * [serge] Fix 1 integration tests regressed by commit bd9509355c8a (PR #47493) (#48426) by @sergereview[bot] in [#48426] * Fix rotary embedding regression (#48477) by @Cyrilvallez in [#48477] * Remove deprecated mask functions (#48476) by @Cyrilvallez in [#48476] * [MTP] Save memory by only capturing the last layer's hidden_states (#48475) by @Cyrilvallez in [#48475] * Allow capturing only necessary hidden_states with capture_outputs (#48081) by @sywangyi in [#48081] * Support per-layer MTP configuration (#48264) by @eladsegal in [#48264] * [docs] Fix code snippets (#47772) by @stevhliu in [#47772] * [Fix] Sparse TikToken tokenizers silently fail (#48446) by @remi-or in [#48446] * No inherit decorator for NeoMME (#48457) by @zucchini-nlp in [#48457] * Batch Rebalance Data Sampler (#47340) by @delock in [#47340] * [serge] Fix 2 integration tests for model `cwm` failing with `import_or_config` (other (2)) (#48414) by @sergereview[bot] in [#48414] * fix: Add DEIMv2 attribution (#48448) by @harshaljanjani in [#48448] * [fix] inkling: mps + cuda mel spec extraction (#47432) by @eustlb in [#47432] * fix: decode() batch path respects self.clean_up_tokenization_spaces (#47793) by @lorenzozanee in [#47793] * Grounding dino fp16 dtype [backlog] (#48438) by @molbap in [#48438] * Init the process group with a load-scaled timeout for sharded loading (#48228) by @qgallouedec in [#48228] * Raise a clear error when a token is both forced and suppressed (#47511) by @qgallouedec in [#47511] * Clarify device placement in pipelines (#47367) by @LysandreJik in [#47367] * Add offload to gradient checkpointing (#48444) by @qgallouedec in [#48444] * [MiniCPMV4_6] Update test_small_model_vision_generation_batch expected output (value drift) (#48406) by @ydshieh in [#48406] * [serge] Fix 2 integration tests for model `hyperclovax` failing with `other` (other (2)) (#48440) by @sergereview[bot] in [#48440] * fix(models): Drop the position-indexed token type lookup in RoPE encoders (#48407) by @harshaljanjani in [#48407] * Document image_hidden_states/pixel_values mutual exclusivity for SmolVLM/Idefics2/Idefics3 (#47714) by @verma8076 in [#47714] * Re-order a bit for easier navigation (#48434) by @zucchini-nlp in [#48434] * Deprecated stuff gone (#48367) by @zucchini-nlp in [#48367] * [serge] Fix 6 integration tests for model `seamless_m4t_v2` failing with `other` (other (6)) (#48425) by @sergereview[bot] in [#48425] * [Docs]: Update GLM 5.3 (#48401) by @Dovis01 in [#48401] * Avoid print to stdout that fails the job `check_failed_tests` job (#48391) by @ydshieh in [#48391] * Fix incorrect tuple return annotations on forward methods returning a Tensor (#48359) by @Gronoxx in [#48359] * Fix interval merge invariant in _find_disjoint (#47860) by @sharmax-vikas in [#47860] * skip mtp slow tests for now (#48328) (#48329) by @tarekziade in [#48329] * Update Tailscale action version in workflow (#48394) by @glegendre01 in [#48394] * fix some failure in xpu (#48252) by @sywangyi in [#48252] * [Improvement] Make gated delta rule more explicit (#47625) by @remi-or in [#47625] * [CB] Fix wrong device scoping (#48370) by @remi-or in [#48370] * Bump transformers-mlinter to 0.1.5 and clear the new findings (#48259) by @tarekziade in [#48259] * fix: flash-attn fallback failing on torch2.13 (#48388) by @NanoCode012 in [#48388] * [LongcatFlash] Fix test_longcat_generation_cpu: use device_map="cpu" to avoid MoE disk offload issue (#48377) by @ydshieh in [#48377] * [Qwen3VLMoe] Update `test_small_model_integration_test_batch` expected output (value drift) (#48376) by @ydshieh in [#48376] * [ONNX] Skip affected models on torch 2.13 (two dynamo regressions) (#48191) by @ydshieh in [#48191] * Fix `safe_open` mmap memory exhaustion on Windows by using `pread` backend (#48341) by @eryk-roch in [#48341] * Fix Zamba2 construction for num_mem_blocks > 1 checkpoints (#48325) by @john-rocky in [#48325] * [Docs] Change 5.3 Flash pos in toc (#48366) by @Dovis01 in [#48366] * [conftest] Use get_cpu_ram_total_gib for psutil patch (cgroup-aware) (#48290) by @ydshieh in [#48290] * Fix flaky test_training_gradient_checkpointing for BigBirdPegasus (fp noise filter) (#48332) by @ydshieh in [#48332] * Quiet continuous batching at default verbosity (#48314) by @qgallouedec in [#48314] * Wait for the first request in the async continuous batching bootstrap (#48304) by @qgallouedec in [#48304] * Ignore a stale best checkpoint recorded in a resumed trainer state (#48319) by @VaggelisGian in [#48319] * [docs] Fix links and remove TokenizerFast (#47748) by @stevhliu in [#47748] * Fix incorrect token classification prefix for ESMC (#48348) by @Rocketknight1 in [#48348] * Create the continuous batching CPU group with local synchronization (#48302) by @qgallouedec in [#48302] * Resolve continuous batching config against the text config for composite models (#48299) by @qgallouedec in [#48299] * [`CI`] Unblock fast CI for now (failing tests) (#48344) by @vasqu in [#48344] * [qwen4_exp] disable torch/onnx export tests due to data-dependent control flow (#48345) by @ydshieh in [#48345] * [debug] Trace previous CI run selection in get_previous_daily_ci.py (#48338) by @ydshieh in [#48338] * Normalize HunYuanVL's legacy field aliases via attribute_map (#48261) by @hmellor in [#48261] ## Significant community contributions The following contributors have made significant changes to the library over the last release: * @ydshieh * [fix] Update stale expected strings in HunYuanVL integration tests (#48646) * [fix] Update stale golden values and fix expected_logits shape in FlavaForPreTraining integration tests (#48639) * [tests] Fix integration test golden values broken by fast image processor default (PR #41388) (#48637) * [KimiLinear] Fix test_cpu_offload: set num_local_experts=4 in model tester (#48624) * Fix GPU memory teardown in CLI serve tests (#48618) * [fix] Fix how we read package versions - triggered by torch 2.14+ (#48615) * [Docker] Upgrade CPU torch to <=2.14.0, torchcodec to <=0.16.0 (#48614) * Add PR comment CI for AMD (MI300) (#48065) * [MiniCPMV4_6] Update test_small_model_vision_generation_batch expected output (value drift) (#48406) * Avoid print to stdout that fails the job `check_failed_tests` job (#48391) * [VibeVoice] Skip generate export tests (flaky) (#48396) * [LongcatFlash] Fix test_longcat_generation_cpu: use device_map="cpu" to avoid MoE disk offload issue (#48377) * [Qwen3VLMoe] Update `test_small_model_integration_test_batch` expected output (value drift) (#48376) * [ONNX] Skip affected models on torch 2.13 (two dynamo regressions) (#48191) * Retry get_daily_ci_runs on stale GitHub API cache (#48374) * [conftest] Use get_cpu_ram_total_gib for psutil patch (cgroup-aware) (#48290) * Fix flaky test_training_gradient_checkpointing for BigBirdPegasus (fp noise filter) (#48332) * [qwen4_exp] disable torch/onnx export tests due to data-dependent control flow (#48345) * [debug] Trace previous CI run selection in get_previous_daily_ci.py (#48338) * @LauraGPT * Add Fun-ASR-Nano model (#46180) * @tarekziade * Fix AttributeError in gradient_checkpointing_enable(offload=True) (#48590) * Compress the agent conventions file and document two modular pitfalls (#48586) * CI: Point test fixtures at hf-internal-testing copies we already host (#48521) * Retire test_multi_gpu_data_parallel_forward (#48508) * QA: Add noisy comment checker (#48484) * skip mtp slow tests for now (#48328) (#48329) * Bump transformers-mlinter to 0.1.5 and clear the new findings (#48259) * @remi-or * [Fix] Fix A10 expectations for a test (#48454) * Kimi linear (#48250) * [Fix] Use dedicated helpers for DeepGEMM and SonicMoE tests (#48523) * [Fix] Sparse TikToken tokenizers silently fail (#48446) * [Improvement] Make gated delta rule more explicit (#47625) * [CB] Fix wrong device scoping (#48370) * [CB] Fail faster (#48334) * @ArthurZucker * Add h4 (#48473) * @harryjulian * Add support for NeuCodec (#47143) * @delock * Batch Rebalance Data Sampler (#47340) * @harshaljanjani * fix: Add DEIMv2 attribution (#48448) * model: Add NVIDIA Canary-1B-v2 to Transformers (#46825) * fix(generation): Enforce the auto-compile cache check for encoder-decoder models (#48364) * fix(models): Drop the position-indexed token type lookup in RoPE encoders (#48407) * @tonywu71 * Add NeoMME and NeoMME-Retriever (#47992) * @Dovis01 * [Docs]: Update GLM 5.3 (#48401) * [Docs] Change 5.3 Flash pos in toc (#48366) * [Glm 5.3 Flash] GLM 5.3 Flash Support (#48342) * @pengzhiliang * Implement VibeVoice (#40546)