transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- update modular parents to more modern detr
- fix(cache): reject unsupported quantized KV-cache rollback
- Save dequantized models without the quantizer's weight conversions
- Fixes an issue related to TP sharding of tied weights
- CI: build-docker-images Doc builder failing: pyarrow requires NumPy>=2.0 but image has 1.26.4
- CI: check_tiny_models failing: `from datasets import load_dataset` ImportError — pyarrow needs NumPy>=2.0 (found 1.26.4)
- CI: Torch pipeline CI failing: 39 pipeline tests fail with RuntimeError ignore_mismatched_sizes=False
- CI: vllm-ci failing: uv 'No solution found' torch==2.14.0+cpu unavailable for vllm cpu build; step uses `sh` with `[[`
- [CLAP] `ClapModel(return_loss=True)` computes the text-to-audio loss twice and never the audio-to-text loss
- `TopHLogitsWarper` does not implement the documented Top-H rule (it bounds the unnormalized partial entropy, and takes H(p) from the top 100 tokens only)
- Docs
- Python not yet supported