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-550 /training_args.bin
- Xet hash:
- e69ec45865b744c3f89bf10f6ad01ebce849cdde2bfc39951745b84d5f8228b9
- Size of remote file:
- 5.91 kB
- SHA256:
- ede5769c73b6c610c4628bbd74325244be057dfbd9cce16276706ada4cb7f175
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