transformers
https://github.com/huggingface/transformers
Python
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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- Issues
- speed up whisper compile time
- DinoV2 is incorrectly documented as a default patch size of 16 instead of 14
- ValueError: Some specified arguments are not used by the HfArgumentParser: ['model_name_or_path', 'show_model/model001', 'train_type', 'use_lora', 'data_path', 'data/AS_2022_train+test', 'per_device_train_batch_size', '1', 'per_device_eval_batch_size', '1', 'num_train_epochs', '5']
- Initializing via AutoImageProcessor before AutoProcessor is imported causes `AttributeError`
- Slow speed when inference LLaMA model with torchao
- fix: unboundlocalerror when trying to retrieve attention feature maps using Qwen2FlashAttention2().forward()
- Sync VQA pipeline with huggingface_hub spec
- Pickled custom model with '.' and trust_remote_code=True and set_start_method("spawn") raises ModuleNotFoundError
- Predicted depth map incorrectly rendered as an image
- Cache: init empty cache when `use_cache`
- Docs
- Python not yet supported