# Locally Hosted ImageBind + Weaviate

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Meta's ImageBind library can be used with a wide range of models for natural language processing. Weaviate seamlessly integrates with the ImageBind library, allowing users to leverage compatible models directly from the Weaviate Database.

These integrations empower developers to build sophisticated AI-driven applications with ease.

## Integrations with ImageBind

Weaviate integrates with the ImageBind model by spinning it up in a container. This allows users to host their own model and use them with Weaviate.

### Embedding models for vector search

![Embedding integration illustration](/assets/docs/weaviate/model-providers/_includes/integration_imagebind_embedding.png)

The ImageBind embedding model transforms multi-modal data into vector embeddings, capturing meaning and context.

[Weaviate integrates with ImageBind's embedding models](imagebind-embeddings-multimodal.md) to enable seamless vectorization of data. This integration allows users to perform semantic and hybrid search operations without the need for additional preprocessing or data transformation steps.

[ImageBind embedding integration page](imagebind-embeddings-multimodal.md)

## Summary

These integrations enable developers to leverage the powerful ImageBind model from directly within Weaviate.

In turn, they simplify the process of building AI-driven applications to speed up your development process, so that you can focus on creating innovative solutions.

## Get started

A locally hosted Weaviate instance is required for these integrations so that you can host your own ImageBind model.

Go to the relevant integration page to learn how to configure Weaviate with the ImageBind model and start using it in your applications.

- [Multimodal Embeddings](imagebind-embeddings-multimodal.md)

## Questions and feedback

Have a question or feedback? Here's how to reach us.

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## Related pages

- [Agents](./agents-index.md)
- [AI-assisted Weaviate code generation](./ai-assisted-vibe-coding-index.md)
- [APIs](./apis-index.md)
- [Authorization and authentication](./authorization-and-authentication-index.md)
- [Benchmarks](./benchmarks-index.md)
- [Best practices](./best-practices-index.md)
- [Client libraries](./clients-index.md)
- [Client Libraries / SDKs](./client-libraries-index.md)
- [Cloud](./cloud-index.md)
- [Cloud account management](./cloud-account-management-index.md)

# Agent Instructions

This portal answers questions programmatically. To receive a synthesized,
source-cited answer instead of crawling page by page, append the `?ask=`
query parameter to any page URL on this site:

    /guides/quickstart?ask=how+do+I+authenticate

Optional parameters:

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- `&version=<label>` scopes the answer to a mounted version when the
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For the full corpus map read `llms.txt` at the site root; for the tool
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