huggingface/transformers Release 5.17.0
Key point
Hugging Face Transformers v5.17.0 introduces support for the 780B parameter HYV4 MoE model and the VibeVoice speech synthesis framework.
Details
Key New Features
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Added HYV4 Model Support: Supports the 780B parameter Mixture-of-Experts (MoE) language model Hy4-Preview. It activates 49B parameters per token and provides a 1M token context window.
- Multi-head Latent Attention (MLA): Compresses keys and values into low-rank latent variables to improve efficiency.
- DeepSeek Sparse Attention (DSA): Uses a lightweight indexer to select the top
index_topkkeys per query. Only layers marked as"full"inindexer_typesrun the indexer, while"shared"layers reuse selections from the previous full layer. - Gated MLA with learnable attention sinks: Each head owns a sink logit that participates in the softmax but contributes no value.
- Independent Hyper-Connections (iHC): Uses
hc_multparallel residual streams instead of a standard residual path, merging and redistributing before and after sublayers. - Note: Multi-token prediction (MTP) layers are not executed, and their weights included in the checkpoint are ignored upon loading (retained for speculative decoding in other runtimes).
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Added VibeVoice Framework Support: Supports the new speech synthesis framework VibeVoice.