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")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/bart-base") model = AutoModel.from_pretrained("facebook/bart-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d5c19b7f0fc1029716ce4c20937c988b83f1c4ba028d46abb80e3ca9a50fdbe
- Size of remote file:
- 558 MB
- SHA256:
- 53dd33667e5835469e2f7e32b51baf2356464ece3b80e3453a4febb83aa79752
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.