Sentence Similarity
Transformers
Safetensors
English
roberta
feature-extraction
security
vulnerability
mitre-attack
cve
bi-encoder
text-embeddings-inference
Instructions to use CIRCL/vulnerability-attack-technique-biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-attack-technique-biencoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-attack-technique-biencoder") model = AutoModel.from_pretrained("CIRCL/vulnerability-attack-technique-biencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d3c0ea05db29438cbf805912b90c1df0c97e0a91a60447de4655c90819585b1
- Size of remote file:
- 499 MB
- SHA256:
- 8478e7820c0fee5d6208ea720075e1f68ac7d3235000f9670e6a216ffd5fbf7c
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