Transformers 发布: Release v5.16.1

来源摘要

# Release v5.16.1 This is a special release as we include GLM! (and a few small fixes) # GLM-5.3-Flash GLM-5.3-Flash, the first **natively multimodal model** in the GLM-5 series. With 320B total parameters and just 18B active parameters, it outperforms GLM-5.2 across benchmarks and real-world workloads at one-tenth the price, while approaching Claude Opus 4.8 on coding and agentic benchmarks. GLM-5.3-Flash starts from a newly trained base model, with its architecture and training recipe redesigned around capability and efficiency. For the first time in the GLM series, we introduce a hybrid architecture combining sparse and linear attention, sharply reducing long-context serving costs while preserving precise long-context capabilities. The model also adopts Manifold-Constrained Hyper-Connections (mHC) to further improve scaling efficiency. Together with our latest **30T-token** multimodal pre-training corpus, these changes enable GLM-5.3-Flash to deliver more intelligence with less compute. **Links:** [Documentation](https://huggingface.co/docs/transformers/main/en/model_doc/glm5_next) * [Glm 5.3 Flash] GLM 5.3 Flash Support (#48342) by @Dovis01 in [#48342](https://github.com/huggingface/transformers/pull/48342) ## Small patch fixes Mainly BC behavior for TP and pinning a hf kernel for security reasons :hugs: - Restore BC for the tensor-parallel API (#48300) by @ArthurZucker - Fix kernel commit and repo paths for ESMFold2 (#48186) by @Rocketknight1 **Full Changelog**: https://github.com/huggingface/transformers/compare/v5.16.0...v5.16.1