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:
- 8a09b75c107f93d3dd8c1fc714e5d6f5afdbf8991479a2b1de72c8ae011cf661
- Size of remote file:
- 499 MB
- SHA256:
- babd5890473a83a2cc134eea6510f56a09e9b665511011c2ddbd1e2d9d7bbf66
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