LLaVA and llama-multimodal-vqa
LLaVA is a foundational vision-language instruction-tuning framework that llama-multimodal-vqa builds upon by adapting its techniques specifically for Llama 3 architecture and VQA tasks.
About LLaVA
haotian-liu/LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
LLaVA helps you understand and interact with images using natural language. You provide an image and ask questions or give instructions about its content, and it generates descriptive text, answers, or performs tasks like segmentation. This is ideal for anyone needing to extract insights from visuals, such as researchers analyzing images, content creators generating descriptions, or operations teams monitoring visual data.
About llama-multimodal-vqa
AdrianBZG/llama-multimodal-vqa
Multimodal Instruction Tuning for Llama 3
This project helps AI developers adapt the Llama 3 language model to understand and respond to questions that require both text and image input. You provide a dataset containing image-text pairs and corresponding question-answer conversations. The output is a fine-tuned Llama 3 model capable of visual question answering. This is for AI engineers or researchers building custom multimodal AI applications.
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