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:
- 4fc87da45d6dd8fa1501ec89d9190b670bb3392ace4fb823de6af4fe826d029e
- Size of remote file:
- 1.01 GB
- SHA256:
- 5bcdee09dd93cdd197e6ea1eee09b9979eaf49d3baada43d87bee36a080a9c8d
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