Text Classification
sentence-transformers
English
numpy
cybersecurity
ai-security
prompt-injection
jailbreak-detection
llm-security
red-team
prompt-defense
ai-firewall
instruction-override
system-prompt-protection
all-MiniLM-L6-v2
hybrid-detection
heuristic-ml-fusion
nlp
security-ai
ai-defense
secure-llm
adversarial-ai
detection-system
Eval Results (legacy)
Instructions to use blackXmask/RedLockX-MiniLM-Malicious-Prompt-Vectors with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use blackXmask/RedLockX-MiniLM-Malicious-Prompt-Vectors with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("blackXmask/RedLockX-MiniLM-Malicious-Prompt-Vectors") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
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