Instructions to use learn3r/bart_memsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use learn3r/bart_memsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("learn3r/bart_memsum") model = AutoModelForSeq2SeqLM.from_pretrained("learn3r/bart_memsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from learn3r/bart_memsum: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/learn3r/bart_memsum/resolve/main/training_args.bin
- Command line
-
hf download hf://learn3r/bart_memsum/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/learn3r/bart_memsum/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 754b84b58ed5606b8a60087bd2ebce88c8be26227dc2678839e13c071d24060f
- Size of remote file:
- 4.22 kB
- SHA256:
- 11aaf05f6ed08bdf8270365deb9cedcc6e7e8c2df9f59cc8990eb1b6dfb4a7f5
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