Instructions to use sujalgawas/codegemma-2b-code-reviewer_V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sujalgawas/codegemma-2b-code-reviewer_V1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sujalgawas/codegemma-2b-code-reviewer_V1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from sujalgawas/codegemma-2b-code-reviewer_V1: direct link, hf CLI and curl.
- Browser
- Download file 29.6 MB
-
https://huggingface.co/sujalgawas/codegemma-2b-code-reviewer_V1/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://sujalgawas/codegemma-2b-code-reviewer_V1/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/sujalgawas/codegemma-2b-code-reviewer_V1/resolve/main/last-checkpoint/optimizer.pt
29.6 MB
- Xet hash:
- 76019447dd3aa49ea5317030cabde26d0a6d8e430a22474fe43e08d7adb6f211
- Size of remote file:
- 29.6 MB
- SHA256:
- bafee975368e71336619df1cf1bdb1ded7df7c25697948013d13a2d6e70f0876
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