Instructions to use notmehul/bart-base-finetuned-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notmehul/bart-base-finetuned-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("notmehul/bart-base-finetuned-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("notmehul/bart-base-finetuned-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from notmehul/bart-base-finetuned-xsum: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/notmehul/bart-base-finetuned-xsum/resolve/main/training_args.bin
- Command line
-
hf download hf://notmehul/bart-base-finetuned-xsum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/notmehul/bart-base-finetuned-xsum/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 0fe2e9e2f040deadb56a0e30fa686ce4dc914a1382c99063de1c9478c72ad45f
- Size of remote file:
- 4.54 kB
- SHA256:
- a84f08be85142453be2ce7d42f413e6b56b999bf2d57ee7ad91105cf4580769e
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