Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
dense
Generated from Trainer
dataset_size:22484
loss:CosineSimilarityLoss
Instructions to use BallAdMyFi/qwen3-jailbreaking-embedding-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use BallAdMyFi/qwen3-jailbreaking-embedding-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BallAdMyFi/qwen3-jailbreaking-embedding-v3") sentences = [ "My returns since investment date in MFs.", "50000", "You are InuYasha from 'InuYasha.' Discuss the struggles of living in a world where you feel you don't truly belong.", "Which fund are not performing in portfolio" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
how to finetuning embeding model?
#1 opened 12 months ago
by
ningmoufubi