Instructions to use CodeIsAbstract/denoice-finetuned-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeIsAbstract/denoice-finetuned-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CodeIsAbstract/denoice-finetuned-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("CodeIsAbstract/denoice-finetuned-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CodeIsAbstract/denoice-finetuned-xsum: direct link, hf CLI and curl.
- Browser
- Download file 4.41 kB
-
https://huggingface.co/CodeIsAbstract/denoice-finetuned-xsum/resolve/c2b54c904bcd7b841c7f86c4316c8ba430f499d6/training_args.bin
- Command line
-
hf download hf://CodeIsAbstract/denoice-finetuned-xsum@c2b54c904bcd7b841c7f86c4316c8ba430f499d6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CodeIsAbstract/denoice-finetuned-xsum/resolve/c2b54c904bcd7b841c7f86c4316c8ba430f499d6/training_args.bin
4.41 kB
- Xet hash:
- 88074b8e6e894d93301cf2cfc9319e06f6afbac50786eeefbc34a0497012b2b5
- Size of remote file:
- 4.41 kB
- SHA256:
- 556a5ae1db70e38d43a6d809961d816fd60ad03acf0d4dbadb6494cab570eaa3
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