Instructions to use dzungpham/graphcodebert-code-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzungpham/graphcodebert-code-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dzungpham/graphcodebert-code-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbb9fa88c12b86170a6a1e36ea55510b87189d555112f5e0e6786bb9e3e31135
- Size of remote file:
- 4.74 MB
- SHA256:
- f6bd93ffc7be4f3b8bae0deb37a8f89d9c0f182a13e967fddb506b0e60950bdf
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