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:
- 8e4ed15054733b963da5685f0ffe80b248b930500b654770216bc42ddb9cba41
- Size of remote file:
- 1.47 kB
- SHA256:
- e3d9e58740bbb7712ef6b1d4dee40c5511fac2847366fd6784a1b91ec00f9680
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