Sentence Similarity
sentence-transformers
ONNX
Safetensors
Transformers.js
modernbert
feature-extraction
embeddings
retrieval
bge-m3
distillation
mmbert
text-embeddings-inference
Instructions to use Horizon-Labs/multilingual-embedding-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Horizon-Labs/multilingual-embedding-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Horizon-Labs/multilingual-embedding-base") sentences = [ "How tall is the Eiffel Tower?", "La tour Eiffel mesure 330 mètres.", "Der Eiffelturm ist das höchste Bauwerk von Paris.", "The Statue of Liberty is 93 metres tall.", "Ich esse gern Pizza." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [5, 5] - Transformers.js
How to use Horizon-Labs/multilingual-embedding-base with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'Horizon-Labs/multilingual-embedding-base'); - Notebooks
- Google Colab
- Kaggle
Ctrl+K