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Llava Int4

Developed by emon-j
LLaVA is a multimodal large model that achieves general-purpose visual assistant capabilities by connecting a visual encoder with a large language model
Downloads 40
Release Time : 11/15/2023

Model Overview

LLaVA connects the CLIP visual encoder with large language models like Vicuna/LLaMa through a simple projection matrix, enabling it to understand and execute both language and image instructions

Model Features

Multimodal Understanding
Processes both visual and language inputs simultaneously, understands image content and generates relevant responses
Simple Architecture Design
Connects pretrained vision and language models through a lightweight projection matrix for efficient multimodal fusion
Instruction Following Capability
Can understand complex multimodal instructions and perform corresponding tasks

Model Capabilities

Image content understanding
Visual question answering
Multimodal dialogue
Image caption generation
Visual instruction execution

Use Cases

Intelligent Assistant
Visual Assistance Q&A
Answers various user questions about image content
Provides accurate and contextually relevant answers
Education
Interactive Learning
Explains complex concepts through image and text interaction
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