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-400 /model.safetensors
- Xet hash:
- 7cf8f0b2b48a960d37b420d30895cf0bb70a67a140430e5126056261879db0a9
- Size of remote file:
- 499 MB
- SHA256:
- 2ee10a85c7345f840ced5553e4c296702832c3b8bc1ad78d1524d2e1e0581559
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