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-450 /model.safetensors
- Xet hash:
- 5b1ecbfd07ff7ddb0f75c7a2d29955efc5f031c6ec53f5821836f6367216cf26
- Size of remote file:
- 499 MB
- SHA256:
- 3547af00f99349378f21a83a224cddcbe0bc25463fe209932447cdb2f07a1a4b
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