Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use CIRCL/vulnerability-attack-technique-classification-pilot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-attack-technique-classification-pilot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/vulnerability-attack-technique-classification-pilot")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-attack-technique-classification-pilot") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-attack-technique-classification-pilot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d48b5ac6c2a2802ccd368251d4cfa06c74427d3ec2d80930da3b6011192427c6
- Size of remote file:
- 5.27 kB
- SHA256:
- f0846c18592fb472562f25da50281e44bf5761ab7760a4ceb4bedff2407a5879
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