Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:203040
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use AryehRotberg/ToS-Sentence-Transformers-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AryehRotberg/ToS-Sentence-Transformers-V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AryehRotberg/ToS-Sentence-Transformers-V2") sentences = [ "Organizing contests, sweeptakes and surveys -Name -Contact details -Marketing preferences information about unsubscribing (if you unsubscribe from our mailing list) -Data provided on the registration or survey form", "Extra data may be collected about you through promotions", "Your personal information is used for many different purposes", "Your data is processed and stored in a country that is friendlier to user privacy protection" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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