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
Download tokenizer.json from CIRCL/vulnerability-attack-technique-biencoder: direct link, hf CLI and curl.
- Browser
- Download file 3.56 MB
-
https://huggingface.co/CIRCL/vulnerability-attack-technique-biencoder/resolve/main/tokenizer.json
- Command line
-
hf download hf://CIRCL/vulnerability-attack-technique-biencoder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CIRCL/vulnerability-attack-technique-biencoder/resolve/main/tokenizer.json
3.56 MB
File too large to display, you can check the raw version instead.