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:
- e980386107f5fd53e0e6e4df55e941a76e87dd65c2d3b02f006e72b644b00f7a
- Size of remote file:
- 1.01 GB
- SHA256:
- 18bda20389f78ad6bfa6581ad9adca9bc87acbf2584831e976eefb0e95f7bcd3
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