Instructions to use codesage/codesage-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesage/codesage-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("codesage/codesage-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from codesage/codesage-base: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/codesage/codesage-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://codesage/codesage-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codesage/codesage-base/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 1a6c881aa937cfba1da2895f7866956c0515993b1a65c3279cb20b62fb45b2c5
- Size of remote file:
- 1.42 GB
- SHA256:
- a04636e2829bb1451e8b4751a13f9a10ef5aa9798e5d1ec4a323ae25eeccf5be
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