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:
- af3b88d8d4264f0e75d51f5442bc4637d5f6df8699d9bf69e0948a6efbd3c374
- Size of remote file:
- 1.01 GB
- SHA256:
- d198b2916f97edec4db8f6e6e1de0fbe2238e1e5f87ecbe27e73cd142a9bec33
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