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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download graphcodebert-focal/checkpoint-200/model.safetensors from dzungpham/graphcodebert-code-classification: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/main/graphcodebert-focal/checkpoint-200/model.safetensors
- Command line
-
hf download hf://dzungpham/graphcodebert-code-classification/graphcodebert-focal/checkpoint-200/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/dzungpham/graphcodebert-code-classification/resolve/main/graphcodebert-focal/checkpoint-200/model.safetensors
499 MB
- Xet hash:
- 3079c7cefac2b2210a93b52d47966e934b31f3dcf81e905b9784d5a15c3feaf2
- Size of remote file:
- 499 MB
- SHA256:
- d51fd56ccff09e10299217033b2ea166baee2ca42845d378e6737c9b07e8e32f
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