Ollama with Vision - Enabling Multimodal RAG


Summary

The video showcases the integration of AMA with Lama 3.2 Vision models, enabling image understanding and processing. It provides a detailed guide on setting up AMA locally and building an end-to-end Rack pipeline. Demonstrations include running Vision models to process images and generate responses based on different prompts, showcasing the model's capabilities effectively. Viewers get a practical insight into interacting with the model within a Rack system and utilizing its retrieval and generation features with visual inputs.


AMA Support for Lama 3.2 Vision

AMA now supports Lama 3.2 Vision models, enabling them to understand and process images as part of the prompt.

Setting up AMA locally

Step-by-step process of setting up AMA locally and building an end-to-end Rack pipeline.

Running Vision Models

Explaining how to run the Vision models and process images, including testing with different image prompts.

Testing Vision Model with Image Prompts

Running tests with different image prompts to showcase the model's capability to understand and generate responses based on vision inputs.

Practical Use of Vision Models

Demonstrating a practical use case of interacting with the Lama 3.2 Vision model within an end-to-end Rack system.

Knowledge Base Interaction

Interacting with the knowledge base using retrieval and generation capabilities of the Vision model.

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