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

It is based on large language models (LLM), 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 the image into a vector representation.
• Language model: takes visual embeddings along with text input and generates a response.

Thus, LLaVA can answer questions about the content of images, describe them, and perform visual and textual tasks.

An example of application is multimodal chatbots, which can understand both text and images simultaneously, for example, answering questions about an image or generating a description.