> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Sentence Transformer Embedder

> Generate local embeddings with the sentence-transformers library.

`SentenceTransformerEmbedder` defaults to `sentence-transformers/all-MiniLM-L6-v2` with 384 dimensions. Models download from Hugging Face on first use and run locally.

```python sentence_transformer_embedder.py theme={null}
from agno.knowledge.embedder.sentence_transformer import SentenceTransformerEmbedder

embedder = SentenceTransformerEmbedder()
embedding = embedder.get_embedding("The quick brown fox jumps over the lazy dog.")

print(embedding[:5])
print(len(embedding))
```

## Run the Example

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno sentence-transformers
```

**2. Run the example**

```bash theme={null}
python sentence_transformer_embedder.py
```

## Developer Resources

* [SentenceTransformerEmbedder reference](https://agno-v2.mintlify.site/reference/knowledge/embedder/sentence-transformer.md)
* [sentence-transformers documentation](https://www.sbert.net/)
* [Embedders overview](https://agno-v2.mintlify.site/knowledge/concepts/embedder/overview.md)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.