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:
- 4b28dc35c85cd3c8b04b7f42916536e9f148dc40d7173d75e4459b97ce282b0f
- Size of remote file:
- 4.74 MB
- SHA256:
- f39cd5d8d518892a6b1e06b53d57c464f4de0ca67339a27037e7e19879adf854
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