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:
- 684f9fbe8d531336a32fc74950e6eb494a1cb92cef6fc81b0285ad4042eb5453
- Size of remote file:
- 499 MB
- SHA256:
- d2d72d7e93f612f723c15f9e85acd7a5972f6d17a5d1fe1ca9bad8acd697f501
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