Instructions to use mahdin70/graphcodebert-devign-code-vulnerability-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahdin70/graphcodebert-devign-code-vulnerability-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mahdin70/graphcodebert-devign-code-vulnerability-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mahdin70/graphcodebert-devign-code-vulnerability-detector") model = AutoModelForSequenceClassification.from_pretrained("mahdin70/graphcodebert-devign-code-vulnerability-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from mahdin70/graphcodebert-devign-code-vulnerability-detector: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/mahdin70/graphcodebert-devign-code-vulnerability-detector/resolve/main/model.safetensors
- Command line
-
hf download hf://mahdin70/graphcodebert-devign-code-vulnerability-detector/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/mahdin70/graphcodebert-devign-code-vulnerability-detector/resolve/main/model.safetensors
499 MB
- Xet hash:
- 2f6d51ac7ff680199e15aa516c9f0607439c9da92ed25217a8cb7caf1e2f2464
- Size of remote file:
- 499 MB
- SHA256:
- d780c4405eda7b5e301770e8360e4406e734124b5d6caaa8e82972df1b891e02
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