Instructions to use arvisioncode/lilt_ls_re_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arvisioncode/lilt_ls_re_en with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import LiLTRobertaLikeForRelationExtraction model = LiLTRobertaLikeForRelationExtraction.from_pretrained("arvisioncode/lilt_ls_re_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arvisioncode/lilt_ls_re_en: direct link, hf CLI and curl.
- Browser
- Download file 2.35 kB
-
https://huggingface.co/arvisioncode/lilt_ls_re_en/resolve/main/training_args.bin
- Command line
-
hf download hf://arvisioncode/lilt_ls_re_en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arvisioncode/lilt_ls_re_en/resolve/main/training_args.bin
2.35 kB
- Xet hash:
- d5ff0975196b9f3b8094ee521bd9c50406e45c42f9467e6104f44b15bb85864f
- Size of remote file:
- 2.35 kB
- SHA256:
- 052abcb941e5c3ac93a8fe3cc83302ce9126efeeecf8dcc9d9f1262daa9961c2
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