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:
- ec58e0e39dacb6b27f3ae584d46c78945a151d8c4333fc003e53ee456dc21d25
- Size of remote file:
- 499 MB
- SHA256:
- 2fd0e615b23c27c3ad62c6b2dc76c1d5bd80aa7bdf6a79b466ded0f58b47f0d5
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