LLaVaOLMoBitnet1B: Ternary LLM goes Multimodal!
Jainaveen Sundaram, Ravishankar Iyer
2024-08-27
Summary
This paper introduces LLaVaOLMoBitnet1B, a new type of language model that can understand both images and text, making it more versatile and efficient for various tasks.
What's the problem?
Many existing large language models (LLMs) are designed to work with either text or images but not both at the same time. Additionally, these models often require powerful computers to run, which can limit their accessibility to users who don't have high-end hardware.
What's the solution?
The authors developed LLaVaOLMoBitnet1B, the first ternary multimodal LLM that can process both images and text together. This model is open-sourced, meaning anyone can use it and contribute to its development. The paper discusses how the model was trained, the challenges faced with ternary models, and future opportunities for improvement.
Why it matters?
This research is important because it makes advanced AI technology more accessible to a wider audience. By allowing a single model to handle multiple types of input effectively, it opens up new possibilities for applications in fields like education, entertainment, and content creation.
Abstract
Multimodal Large Language Models (MM-LLMs) have seen significant advancements in the last year, demonstrating impressive performance across tasks. However, to truly democratize AI, models must exhibit strong capabilities and be able to run efficiently on small compute footprints accessible by most. Part of this quest, we introduce LLaVaOLMoBitnet1B - the first Ternary Multimodal LLM capable of accepting Image(s)+Text inputs to produce coherent textual responses. The model is fully open-sourced along with training scripts to encourage further research in this space. This accompanying technical report highlights the training process, evaluation details, challenges associated with ternary models and future opportunities. Link to the model: https://huggingface.co/IntelLabs/LlavaOLMoBitnet1B