Instructions to use byeongal/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use byeongal/bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="byeongal/bart-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("byeongal/bart-base") model = AutoModel.from_pretrained("byeongal/bart-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from byeongal/bart-base: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/byeongal/bart-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://byeongal/bart-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/byeongal/bart-base/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- d0b0d4761a25b3eee5e1f3ae9ab2576284dc18e36753c46834defe2c5020a5bc
- Size of remote file:
- 558 MB
- SHA256:
- c393f632913cdc64c13fcd1b039a74f17dd83cc3029c556802c0f2f8792b46f9
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