transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- MultiModalityCausalLM does not support Flash Attention 2.0 yet
- 'do_sample' model default cannot be overridden
- Add support for post-processing kwargs in image-text-to-text pipeline
- Fix: bamba error handling kwargs with forward pass
- Support modernBERT for encoder-decoder models
- Model loaded with `PretrainedModel.from_pretrained` and `with torch.device("cuda"):` decorator leads to unexpected errors compared to `.to("cuda")`
- `inv_freq_expanded` does not move to correct device in Qwen2
- Default value for mean_resizing in resize_token_embeddings should be False
- FineTuning AutoModelForSequenceClassification.from_pretrained(meta-llama/Llama-3.2-1B) Bug:RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0! (when checking argument for argument target in method wrapper_CUDA_nll_loss_forward) and awq importing
- [`Mamba2`] Varlen implementation
- Docs
- Python not yet supported