Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:167508
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use AryehRotberg/ToS-Sentence-Transformers-V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AryehRotberg/ToS-Sentence-Transformers-V3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AryehRotberg/ToS-Sentence-Transformers-V3") sentences = [ "We operate globally and may transfer your personal information", "Content you post may be edited by the service for any reason", "You can retrieve an archive of your data", "Your data may be processed and stored anywhere in the world" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle