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:
- 3ee2264822c77b920063eb5cea7b06f562da6ee3a508ffa6ecc6041916345ae8
- Size of remote file:
- 4.74 MB
- SHA256:
- 3e0f890ee01e658e09411ac4671fa7e6acf6add3a66c2dbe04247a90ddcb4106
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