Multimodal model research for GPT4-style training
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This repository provides the Lynx model, an 8B parameter large language model designed for multimodal understanding of images and videos. It addresses the challenges of integrating visual information into LLMs, targeting researchers and developers working on multimodal AI applications. The project offers a framework for training and evaluating such models, with released checkpoints and benchmark results.
How It Works
Lynx integrates visual features from a Vision Transformer (EVA-CLIP ViT-G) into a Vicuna-7B language model. This approach allows the LLM to process and reason about visual content alongside text. The model architecture and training methodology are detailed in an accompanying arXiv paper, focusing on key factors for effective multimodal LLM training.
Quick Start & Requirements
conda env create -f environment.yml
followed by conda activate lynx
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Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
The setup process is complex, requiring manual downloading and organization of multiple large datasets and model checkpoints. The project is presented as a research release, and extensive user support beyond GitHub issues is not explicitly stated.
2 years ago
1 day