Instructions to use codesage/codesage-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesage/codesage-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("codesage/codesage-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from codesage/codesage-small: direct link, hf CLI and curl.
- Browser
- Download file 512 MB
-
https://huggingface.co/codesage/codesage-small/resolve/d4c8b2db0835ed7047fa6db08bb231b6f86586b0/pytorch_model.bin
- Command line
-
hf download hf://codesage/codesage-small@d4c8b2db0835ed7047fa6db08bb231b6f86586b0/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codesage/codesage-small/resolve/d4c8b2db0835ed7047fa6db08bb231b6f86586b0/pytorch_model.bin
512 MB
- Xet hash:
- a517701e85ae35f2c20042f5d0751d0aa7b01543a9ca860cc6d66bbdb5980d8e
- Size of remote file:
- 512 MB
- SHA256:
- ae7a59fb53f85f5f46ab28109063153787783cac269b1dfbf69ab15478442d6a
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