Instructions to use rvashurin/bart_base_xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rvashurin/bart_base_xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rvashurin/bart_base_xsum") model = AutoModelForSeq2SeqLM.from_pretrained("rvashurin/bart_base_xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rvashurin/bart_base_xsum: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/rvashurin/bart_base_xsum/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rvashurin/bart_base_xsum/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rvashurin/bart_base_xsum/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- e547174ae88feea3957b9741f95a43a000437ce419cd990e81ade07196050fda
- Size of remote file:
- 558 MB
- SHA256:
- bc9c8d37b841e35efebdbb4301f7e28d40aab7a1a90580bfc7ee50e9d02123f5
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