Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:971
loss:OnlineContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use srikarvar/multilingual-e5-small-pairclass-2 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-2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("srikarvar/multilingual-e5-small-pairclass-2") sentences = [ "How to bake a pie?", "Steps to bake a pie", "What are the ingredients of pizza?", "Steps to draft a business plan" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K