Instructions to use roofdancer/thesis-bart-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roofdancer/thesis-bart-finetuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("roofdancer/thesis-bart-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("roofdancer/thesis-bart-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from roofdancer/thesis-bart-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/roofdancer/thesis-bart-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://roofdancer/thesis-bart-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/roofdancer/thesis-bart-finetuned/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- c50bd310f1f3040101ae42694c65ef104d3c33a1108fe058044bee744760c996
- Size of remote file:
- 5.05 kB
- SHA256:
- 377dc8c474cbf38c63fe7c6eb60ad7be70257a753bca67e407de97aa5784d714
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