Instructions to use psxjp5/bart-large-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psxjp5/bart-large-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/bart-large-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("psxjp5/bart-large-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from psxjp5/bart-large-xsum: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/psxjp5/bart-large-xsum/resolve/main/training_args.bin
- Command line
-
hf download hf://psxjp5/bart-large-xsum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/psxjp5/bart-large-xsum/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 11aad9bf7cedafe02377aa6facd762162f5e3e71fbf3e7b4dc60dc47b8f7c11c
- Size of remote file:
- 4.16 kB
- SHA256:
- 47eea654ed284721f14c5acbff018cb4321331846bd881c0022493e3b1f0fe68
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