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:
- 1eef4163e7fd8c9f35106121c5fc37b8bcbb53745e725edc1bd3ccd79ea86159
- Size of remote file:
- 14.6 kB
- SHA256:
- 13732907e73a399dc511f6dc40d1789e18310f4a4b02a554d9781e58f5609487
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