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:
- 4a1bab0fd120dc2a1e065510f7294ee89a93ae33c3c11e29799b19c47374a6c6
- Size of remote file:
- 14.6 kB
- SHA256:
- 7f20a6bc329e0a09a02cfaa878042a26d58ee96eb6fa0372eb67bd380a494157
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