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:
- ceb2b5740266db8110c9e31cc66c2c64a07a7e356c9abb44d60792667286eff8
- Size of remote file:
- 499 MB
- SHA256:
- 7e7d793b00b82762534dd7938db3576dd0662986bacde6b42905b25792458d17
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