Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:296
loss:ContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use srikarvar/multilingual-e5-small-pairclass-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-pairclass-contrastive with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srikarvar/multilingual-e5-small-pairclass-contrastive") sentences = [ "Biography of Queen Elisabeth II", "Biography of Queen Elisabeth I", "What are the ingredients of a pizza?", "When was the Declaration of Independence signed?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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