Instructions to use lilferrit/ft-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilferrit/ft-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lilferrit/ft-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("lilferrit/ft-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lilferrit/ft-xsum: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/lilferrit/ft-xsum/resolve/main/training_args.bin
- Command line
-
hf download hf://lilferrit/ft-xsum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lilferrit/ft-xsum/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 656bcbc550d860230c73746ada2a8f00a7173522cb309c4ce17c33125a5a61ac
- Size of remote file:
- 5.18 kB
- SHA256:
- 98c466bda9bc078b62f0161b5e7526bcba7dfebe839c6b76f7dfad7adf5a7710
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