Instructions to use codesage/codesage-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codesage/codesage-base-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import CodeSage model = CodeSage.from_pretrained("codesage/codesage-base-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from codesage/codesage-base-v2: direct link, hf CLI and curl.
- Browser
- Download file 710 MB
-
https://huggingface.co/codesage/codesage-base-v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://codesage/codesage-base-v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/codesage/codesage-base-v2/resolve/main/pytorch_model.bin
710 MB
- Xet hash:
- 1179c16c14382b9958b7886be0e6c48e94ae118c7c5bb3e93a1acfba89bee9a3
- Size of remote file:
- 710 MB
- SHA256:
- 4a3ec46f2ba2027c541e159b4f1598ddbc4043ad41ac2b1f704adc69b96bcbfe
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