transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- Fix convert_tokens_to_string when decoder is None
- should use eigvalsh instead of eigvals for fast&stable covariance matrix diagonalization
- Feature to configure `stop_strings` in `generation_config.json` or other config files
- RuntimeError: linalg.vector_norm: Expected a floating point or complex tensor as input. Got Long
- when model.generate with num_beams=2 and num_return_sequences=2,the output seqs are different from input_ids of stopping_criteria
- Unhandled 'num_items_in_batch' in Mistral model
- Handle num_items_in_batch in Mistral's forward
- Mismatched keyword argument names of llama make GA fix invalid
- uniformize kwargs for SAM
- Does per_device_train_batch_size have a loss error similar to that of GA?
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