Instructions to use JulianS/bart-base-finetuned-summscreen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JulianS/bart-base-finetuned-summscreen with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JulianS/bart-base-finetuned-summscreen") model = AutoModelForSeq2SeqLM.from_pretrained("JulianS/bart-base-finetuned-summscreen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from JulianS/bart-base-finetuned-summscreen: direct link, hf CLI and curl.
- Browser
- Download file 3.71 kB
-
https://huggingface.co/JulianS/bart-base-finetuned-summscreen/resolve/main/training_args.bin
- Command line
-
hf download hf://JulianS/bart-base-finetuned-summscreen/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/JulianS/bart-base-finetuned-summscreen/resolve/main/training_args.bin
3.71 kB
- Xet hash:
- fd8a077b1fd3493cf87c4175d92336abac8ccc1a776976b7e8716e828f15cc8c
- Size of remote file:
- 3.71 kB
- SHA256:
- e0f4b2b09bae7c86eeb423b0600e47b666dbab977979830a557e5fe2800d82c5
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