Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
Generated from Trainer
dataset_size:42977
loss:MatryoshkaLoss
loss:CachedMultipleNegativesRankingLoss
Eval Results (legacy)
Not-For-All-Audiences
Instructions to use Hyphonical/Qwen3-VL-Embedding-2B-NSFW with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Hyphonical/Qwen3-VL-Embedding-2B-NSFW with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Hyphonical/Qwen3-VL-Embedding-2B-NSFW") sentences = [ "A muscular, nude man with big, veiny cock and large pecs flexes his biceps and traps while his bara chest, complete with visible male nipples and pubic hair, rises and falls with a hard erection.", "./Images/12604035.jpg", "./Images/11882380.jpg", "./Images/12535412.jpg", "./Images/12450474.jpg", "./Images/12604909.jpg" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [6, 6] - Notebooks
- Google Colab
- Kaggle
Not-For-All-Audiences
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