Instructions to use transZ/BART_shared_clean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transZ/BART_shared_clean with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("transZ/BART_shared_clean", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from transZ/BART_shared_clean: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/transZ/BART_shared_clean/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://transZ/BART_shared_clean/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/transZ/BART_shared_clean/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- c4c13552cec76fd72bf2a8068b2d652b4bb78f8b7f5925dff36f2a4d20054c39
- Size of remote file:
- 558 MB
- SHA256:
- 896052ee8770a58c32ec53429b48a599a494f69738e85626c31e6e2cbeb51847
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