# Nomic AI

On Epsilla Cloud, you can enable Nomic AI integration by providing your Nomic 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-bb00f4395749aff8b302f7fee314cb97ecc5dd19%2FScreenshot%202024-02-13%20at%2011.21.53%20AM.png?alt=media" alt=""><figcaption></figcaption></figure>

## Embeddings

Epsilla integrates with Nomic AI with the following embedding models.

<table><thead><tr><th width="322">Name</th><th width="133">Dimensions</th><th>Support Dimension Reduction</th></tr></thead><tbody><tr><td><strong>nomicai/nomic-embed-text-v1.5</strong></td><td>768</td><td>Yes</td></tr><tr><td><strong>nomicai/nomic-embed-text-v1</strong></td><td>768</td><td>No</td></tr></tbody></table>

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#nomic-ai-embedding).

Then you can start using the nomicai 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-ac735df089427264584be4fa7c25a58f6ef32ee0%2FScreenshot%202024-02-13%20at%2011.23.30%20AM.png?alt=media" alt=""><figcaption></figcaption></figure>

For models that support dimension reduction, you can optionally provide a dimensions parameter to reduce the embedding response size:

<figure><img src="https://2532879721-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FM0ZX7fId7ifK45ldHWEp%2Fuploads%2Fgit-blob-52cf25b0a52d890fa11874a0058460b16cf51d79%2FScreenshot%202024-02-14%20at%204.23.37%20PM.png?alt=media" alt=""><figcaption></figcaption></figure>