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 vocab.json from jacpacd/vuln-detector-codebert: direct link, hf CLI and curl.
- Browser
- Download file 798 kB
-
https://huggingface.co/jacpacd/vuln-detector-codebert/resolve/487901714ed7eaf6b20def66958f2d6f54567a42/vocab.json
- Command line
-
hf download hf://jacpacd/vuln-detector-codebert@487901714ed7eaf6b20def66958f2d6f54567a42/vocab.json
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curl -L -o vocab.json https://huggingface.co/jacpacd/vuln-detector-codebert/resolve/487901714ed7eaf6b20def66958f2d6f54567a42/vocab.json
798 kB
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