transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- Restore .item() on the packed-path max_seqlen (third site missed by #47134)
- This PR generalizes continuous batching graph support from CUDA-only …
- Branch aware export
- handle transpose during model loading with TP (Qwen3-VL-MoE)
- Register kimi_k2 as a native deepseek_v3 alias
- Fix fp8 dtype
- Continuous batching does not support hybrid linear-attention models (all Qwen3.5/3.6/3.8)
- Native TP breaks on Qwen3.5/3.6 hybrids: reshape error in linear-attention layers
- Native TP has no KV-head replication: tp_size > num_key_value_heads fails mid-forward
- Byte-level tokenizer.json + Hub tokenizer_class LlamaTokenizer/Fast
- Docs
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