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:
- faf3eb2d2770da2bc149874890a1bcc569f32fa1ef22e31285eedf29b60516fb
- Size of remote file:
- 1.47 kB
- SHA256:
- 96aef0834a2bf334a9c09519b222fef1c3fbdcfbb4b3962aeae8d3e2cd7b8901
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