Image Q&A with IBM watsonx and multimodal Llama 3.2
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Learn how to create an image Q&A system using IBM watsonx and the multimodal Llama 3.2 model. Integrate computer vision and natural language processing to build an interactive AI-driven application.
At a Glance
Learn how to code a simple image Q&A system using IBM watsonx and Llama 3.2 in this quick 30-minute project. You’ll learn how to set up and run a model that answers questions about images, making it easy to see how multimodal LLMs can bridge the gap between visuals and language. This project is straightforward and perfect for developers or AI enthusiasts who want to build practical, interactive tools with minimal effort.
response:
The image contains a logo for the “Skills Network” with a purple and grey color scheme. The logo features a stylized tree in the center, surrounded by a circle. The tree has a few branches and leaves, and is depicted in a simple, line-art style. The circle surrounding the tree is also stylized, with a subtle gradient effect that gives it a sense of depth and dimensionality. Overall, the logo is clean and modern, conveying a sense of professionalism and sophistication.
What you’ll learn
– Understand the integration of natural language processing and computer vision in creating advanced AI applications.
– Have the ability to use IBM watsonx and LLaMA-3-2-11b-Vision-Instruct in a practical, notebook-based environment.
– Gain insights into the application of AI technologies for educational and business purposes.
What you’ll need
– A basic understanding of Python
– The latest version of Chrome, Edge, Firefox, Internet Explorer, or Safari web browser
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