Qwen2-VL-7B-VLGuard Open-source Multimodal Model - Freely Deployed to Solve Secure Visual Question Answering Tasks

Qwen2 VL 7B VLGuard

Developed by Foreshhh

A multimodal vision-language model fine-tuned on the VLGuard dataset based on Qwen2-VL-7B, focusing on safety-related visual question answering tasks.

Text-to-Image

Safetensors

EnglishOpen Source License:Apache-2.0 #Multimodal Safety Q&A #Vision-Language Joint Reasoning #7B Parameter Efficient Fine-Tuning

Downloads 24

Release Time : 12/16/2024

Model Overview

This model is a multimodal large language model that combines visual and language understanding capabilities, specifically designed for safety-related visual question answering tasks.

Model Features

Multimodal Understanding

Capable of processing both image and text inputs, understanding visual and linguistic information.

Safety-Oriented

Specifically optimized for safety-related visual question answering tasks.

Large-Scale Pretraining

Based on a large-scale pretrained model with 7B parameters, offering strong generalization capabilities.

Model Capabilities

Visual Question Answering

Image Understanding

Text Understanding

Multimodal Reasoning

Use Cases

Security Monitoring

Anomaly Behavior Recognition

Identify potential security threats or abnormal behaviors by analyzing surveillance images.

Content Moderation

Inappropriate Content Detection

Identify potentially inappropriate or prohibited content in images.

Property	Details
Model Type	Fine - tuned Qwen2-VL-7B for visual question - answering
Training Data	VLGuard dataset

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Qwen2 VL 7B VLGuard

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Visual Question Answering Model

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Model Information

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