Instructions to use transZ/BART_shared_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/BART_shared_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("transZ/BART_shared_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from transZ/BART_shared_v2: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/transZ/BART_shared_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://transZ/BART_shared_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/transZ/BART_shared_v2/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 5a83436db86fdf3f869206e092344a53fabec4463276c7aa98ef350716ec9522
- Size of remote file:
- 558 MB
- SHA256:
- 318575718817af627faf74d135b04e64970ce3d999333a1932745214b6a7fd3f
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