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
graphcodebert-code-classification / graphcodebert-base-lowLR-highBatchSize /checkpoint-300 /model.safetensors
- Xet hash:
- 64a5c892a9a9b82c236d41e7c6d28e5a84070e736abca6e349a672ff3dacb185
- Size of remote file:
- 499 MB
- SHA256:
- 887ddaff8ed9f2847ee48b07006fe44accd881ddff639ed716d714b0d8cbba1e
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