Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
classification
nlp
vulnerability
Eval Results (legacy)
text-embeddings-inference
Instructions to use CIRCL/vulnerability-severity-classification-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-severity-classification-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/vulnerability-severity-classification-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 1,014 Bytes
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2026-10-29T18:04:54,VulnTrain,a0de6b0a-1c64-47a0-ac0e-f7afb09977be,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,15907.370135360998,0.48498217400176347,3.04878914537659e-05,70.00019464846667,903.8459795071008,70.0,0.30927252797905813,3.989522156337392,0.30854287970663974,4.607337564023099,0.0,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-147-generic-x86_64-with-glibc2.39,3.12.3,3.3.2,224,Intel(R) Xeon(R) Platinum 8480+,4,4 x NVIDIA L40S,6.1327,49.6098,2015.3354148864746,machine,0.693132613772644,77.6417187401376,1.0988322918639148,21.301271207569027,N,1.0,0.0
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