TinyGPT-V: Efficient Multimodal Large Language Model via Small Backbones

arXiv:2312.16862v2 Announce Type: replace
Abstract: In recent years, multimodal large language models (MLLMs) such as GPT-4V have demonstrated remarkable advancements, excelling in a variety of vision-language tasks. Despite their prowess, the closed-source nature and computational demands of such models limit their accessibility and applicability. This study introduces TinyGPT-V, a novel open-source MLLM, designed for efficient training and inference across various vision-language tasks, including image captioning (IC) and visual question answering (VQA). Leveraging a compact yet powerful architecture, TinyGPT-V integrates the …

arxiv cs.cl cs.cv language language model large language large language model multimodal multimodal large language model small tinygpt-v type via