LLaMA-VID Multimodal Chatbot Open-Sourced! Supports Processing Videos Up to Several Hours Long and Free to Use

Llama Vid 7b Full 224 Video Fps 1

Developed by YanweiLi

LLaMA-VID is an open-source multimodal chatbot fine-tuned from LLaMA/Vicuna, supporting hours-long video processing through extended context tokens.

Text-to-Video

Transformers

#Ultra-long video understanding #Multimodal instruction following #For academic research

Downloads 86

Release Time : 11/29/2023

Model Overview

LLaMA-VID is a vision-language model that empowers existing frameworks with additional context tokens to handle ultra-long videos and break performance limits. Implemented based on the LLaVA architecture, it is primarily used for academic research in large multimodal models and chatbots.

Model Features

Ultra-long video processing

Supports processing hours-long video content through extended context tokens

Multimodal understanding

Processes both video and text information simultaneously for cross-modal understanding

Open-source architecture

Built upon open-source LLaMA/Vicuna and LLaVA architectures

Model Capabilities

Video content understanding

Multimodal dialogue

Long video analysis

Visual question answering

Use Cases

Academic research

Video understanding research

Used for research at the intersection of computer vision and natural language processing

Multimodal model development

Serves as a foundation for developing more advanced multimodal models

Education

Educational video analysis

Automatically analyzes long educational video content and answers related questions

Property	Details
Model Type	LLaMA-VID is an open-source chatbot trained by fine-tuning LLaMA/Vicuna on GPT-generated multimodal instruction-following data. It empowers existing frameworks to support hour-long videos and pushes their upper limit with an extra context token. This repo is built based on LLaVA.
Model Date	llama-vid-7b-full-224-video-fps-1 was trained on 11/2023.

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Llama Vid 7b Full 224 Video Fps 1

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🚀 LLaMA-VID Model Card

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