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:
- 98995d32d9c351db9124a3c03bf47e7c5b5b33399e282f0a3bb869ee592bd204
- Size of remote file:
- 499 MB
- SHA256:
- d063dd827bd14bb9ea9021ac3203ca6eeb75950097af9e82d2df0faf2713a046
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