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NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different sensory formats and generate responses in different media types. This architecture allows the model to convert between modalities, such as generating images from text descriptions or producing audio or video outputs based on textual prompts. The project also introduces instruction-tuning strategies that enable the model to perform complex multimodal reasoning and generation tasks with minimal additional parameters.
Features
- Any-to-any multimodal input and output across text, images, video, and audio
- Integration of language models with multimodal encoders and diffusion decoders
- Instruction-tuning framework for multimodal reasoning tasks
- Architecture designed for cross-modal content generation and understanding
- Efficient parameter tuning using modular projection layers
- Research environment for developing advanced multimodal AI systems
Project Samples
