Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:200
loss:OnlineContrastiveLoss
text-embeddings-inference
Not-For-All-Audiences
Instructions to use KGESH/nsfw-bge-m3-v6e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KGESH/nsfw-bge-m3-v6e with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KGESH/nsfw-bge-m3-v6e") sentences = [ "bondage", "shibari", "Japanese noodle soup", "pastry" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Not-For-All-Audiences
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