LLaVaOLMoBitnet1B: Ternary LLM goes Multimodal!

Jainaveen Sundaram; Ravishankar Iyer

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Paper · arXiv 2408.13402

LLaVaOLMoBitnet1B: Ternary LLM goes Multimodal!

Jainaveen Sundaram, Ravishankar Iyer

18 upvotesAugust 23, 2024arXiv 预印本

AI 摘要

LLaVaOLMoBitnet1B is the first open-source ternary multimodal LLM that processes images and text to generate coherent responses, designed to run efficiently on small computational resources.

Multimodal Large Language ModelsMM-LLMsTernary Multimodal LLM

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