# Mixedbread AI

On Epsilla Cloud, you can enable Mixedbread AI integration by providing your Mixedbread AI API key (we securely manage your keys using AWS KMS):

<figure><img src="https://2532879721-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FM0ZX7fId7ifK45ldHWEp%2Fuploads%2Fgit-blob-606c13e7a817c30663b29c1f9b083a88d272db87%2FScreenshot%202024-02-13%20at%2011.21.29%20AM.png?alt=media" alt=""><figcaption></figcaption></figure>

## Embeddings

Epsilla integrates with Mixedbread AI with the following embedding models.

| Name                                   | Dimensions |
| -------------------------------------- | ---------- |
| **mixedbreadai/UAE-Large-V1**          | 1024       |
| **mixedbreadai/bge-large-en-v1.5**     | 1024       |
| **mixedbreadai/gte-large**             | 1024       |
| **mixedbreadai/e5-large-v2**           | 1024       |
| **mixedbreadai/multilingual-e5-large** | 1024       |
| **mixedbreadai/multilingual-e5-base**  | 768        |
| **mixedbreadai/gte-large-zh**          | 1024       |

For Epsilla open source vector db, you just need to add a header in the data ingestion and semantic search queries [like this](https://epsilla-inc.gitbook.io/epsilladb/advanced-topics/embeddings#mixedbread-ai-embedding).

Then you can start using the mixedbreadai embedding model during vector table schema creation:

<figure><img src="https://2532879721-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FM0ZX7fId7ifK45ldHWEp%2Fuploads%2Fgit-blob-a939b2793d975374ed74534315d45244a4901a9f%2FScreenshot%202024-02-13%20at%2011.23.10%20AM.png?alt=media" alt=""><figcaption></figcaption></figure>