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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jacpacd/vuln-detector-codebert") model = AutoModelForSequenceClassification.from_pretrained("jacpacd/vuln-detector-codebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jacpacd/vuln-detector-codebert: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/jacpacd/vuln-detector-codebert/resolve/main/tokenizer.json
- Command line
-
hf download hf://jacpacd/vuln-detector-codebert/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/jacpacd/vuln-detector-codebert/resolve/main/tokenizer.json
3.56 MB
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