Text Classification
Transformers
Safetensors
code
roberta
code-classification
vulnerability-detection
automatic-vulnerability-detection
secure-coding
text-embeddings-inference
Instructions to use jacpacd/vuln-detector-codebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacpacd/vuln-detector-codebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jacpacd/vuln-detector-codebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jacpacd/vuln-detector-codebert") model = AutoModelForSequenceClassification.from_pretrained("jacpacd/vuln-detector-codebert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20fbc06dfc8247a8e908f8c5fb964f63bad31e09624b808be6f39b0d144854c6
- Size of remote file:
- 5.71 kB
- SHA256:
- e10e5e6e2ab894f6e86121bdafa54e285299183dd9f46816ab187fdcf6d42053
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