Instructions to use arrow-hf/bart-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arrow-hf/bart-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="arrow-hf/bart-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("arrow-hf/bart-large") model = AutoModel.from_pretrained("arrow-hf/bart-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.5f05823 -
Update README: reflect full mirror (model weights + tokenizer + ONNX)
Verified signature6e25fa9 -
Full mirror of facebook/bart-large (snapshot_download)
Verified signatureb3764c9 -
Mirror facebook/bart-large tokenizer files
Verified signature6b31f3d -
initial commit
Verified signature153e08e