What is LLaVA and how is it structured?

LLaVA (Large Language and Vision Assistant) is a multimodal model that combines text and image processing to solve tasks requiring understanding and generating information based on both types of data.

It is built on large language models (LLMs), such as GPT, and integrates visual data through specialized architectures, such as visual encoders (e.g., ViT — Vision Transformer).

Main components of LLaVA:

• Visual encoder: converts an image into a vector representation.
• Language model: takes visual embeddings along with text input and generates a response.

Thus, LLaVA can answer questions about image content, describe images, and perform visual-textual tasks.

An example application is multimodal chatbots that can understand both text and images simultaneously, such as answering questions about a picture or generating descriptions.