Instructions to use facebook/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/bart-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/bart-base") model = AutoModel.from_pretrained("facebook/bart-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.safetensors from facebook/bart-base: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/facebook/bart-base/resolve/main/model.safetensors
- Command line
-
hf download hf://facebook/bart-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/facebook/bart-base/resolve/main/model.safetensors
558 MB
- Xet hash:
- e0f8134343cb241a14e2fbebc8ff53f12faf1e8ab2e0d27bff0d44b2ac561ed0
- Size of remote file:
- 558 MB
- SHA256:
- 1bd3ac8e5b3ac71c77cf18fbcd8b113e0bfceced94c5cfbbb9a2b4bb4781190b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.