Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:333
loss:ContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use srikarvar/multilingual-e5-small-cogcache-contrastive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use srikarvar/multilingual-e5-small-cogcache-contrastive with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srikarvar/multilingual-e5-small-cogcache-contrastive") sentences = [ "What is the capital of Canada?", "Main ingredient in guacamole", "Prime Minister of the United Kingdom", "What is the capital of Australia?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 349 Bytes
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