# Sentence Transformers — State-of-the-Art Embeddings

> Sentence Transformers computes text embeddings for semantic search, similarity, and reranking. 18.5K+ GitHub stars. 15,000+ pre-trained models, dense/sparse/reranker, multi-lingual. Apache 2.0.

## Install

Save as a script file and run:

## Quick Use

```bash
# Install
pip install -U sentence-transformers

# Compute embeddings
python -c "
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('all-MiniLM-L6-v2')
sentences = ['AI is amazing', 'Vector search is fast', 'I love pizza']
embeddings = model.encode(sentences)
from sentence_transformers.util import cos_sim
print(cos_sim(embeddings[0], embeddings[1]))  # High similarity
print(cos_sim(embeddings[0], embeddings[2]))  # Low similarity
"
```

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## Intro

Sentence Transformers is the standard Python framework for computing state-of-the-art text embeddings, enabling semantic search, text similarity, clustering, and reranking. With 18,500+ GitHub stars and Apache 2.0 license, it provides access to 15,000+ pre-trained models on Hugging Face, supports dense, sparse, and reranker embedding models, multi-lingual capabilities, and training support for custom models. Used by thousands of production applications for semantic search and RAG pipelines.

**Best for**: Developers building semantic search, RAG, text clustering, or similarity applications
**Works with**: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf
**Models**: 15,000+ pre-trained on Hugging Face Hub

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## Key Features

- **15,000+ models**: Pre-trained embeddings on Hugging Face Hub
- **Dense + sparse + reranker**: Multiple embedding strategies
- **Semantic search**: Encode queries and documents for similarity matching
- **Multi-lingual**: Cross-language embedding support
- **Custom training**: Fine-tune models on your own data
- **Clustering + paraphrase mining**: Built-in applications

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### FAQ

**Q: What is Sentence Transformers?**
A: The standard embedding framework with 18.5K+ stars. 15,000+ pre-trained models for semantic search, similarity, and reranking. Dense, sparse, and multi-lingual. Apache 2.0.

**Q: How do I install it?**
A: `pip install -U sentence-transformers`. Then `SentenceTransformer('all-MiniLM-L6-v2').encode(texts)`.

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## Source & Thanks

> Created by [UKP Lab](https://github.com/UKPLab). Licensed under Apache 2.0.
> [UKPLab/sentence-transformers](https://github.com/UKPLab/sentence-transformers) — 18,500+ GitHub stars

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Source: https://tokrepo.com/en/workflows/596096ff-e0fb-41bd-a964-03817dafce9d
Author: Script Depot