Instructions to use codesage/codesage-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesage/codesage-small-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("codesage/codesage-small-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from codesage/codesage-small-v2: direct link, hf CLI and curl.
- Browser
- Download file 256 MB
-
https://huggingface.co/codesage/codesage-small-v2/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://codesage/codesage-small-v2@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codesage/codesage-small-v2/resolve/refs%2Fpr%2F4/pytorch_model.bin
256 MB
- Xet hash:
- a7da48563a1178fa942796790b020f1050a3fd23b312dd26f127e797af8e4bc5
- Size of remote file:
- 256 MB
- SHA256:
- c6ed7fe6ee8a40b7830482c91421733f4c66c6e128adfc87dd9cee1a41936c14
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