R1-VL-7B Open-source Inference Model - Free Deployment to Facilitate Efficient Image-to-Text and Video-to-Text Conversion

R1 VL 7B

Developed by jingyiZ00

R1-VL-7B is an inference model based on Qwen2-VL-7B-Instruct, trained using the Stepwise Grouped Relative Policy Optimization (StepGRPO) method, focusing on the image-text to text task.

Image-to-Text

Transformers

Open Source License:Apache-2.0 #Multimodal reasoning #Step-by-step optimization strategy #Image-text understanding

Downloads 1,729

Release Time : 3/18/2025

Model Overview

R1-VL-7B is a vision-language inference model that can process image and text inputs and generate corresponding text outputs. It is mainly used for image-text understanding and inference tasks.

Model Features

Stepwise Grouped Relative Policy Optimization

Using the StepGRPO training method may improve the model's inference ability and training efficiency

Vision-language understanding

Capable of simultaneously processing image and text inputs for cross-modal understanding

Based on the Qwen2-VL architecture

Built on the powerful Qwen2-VL-7B-Instruct base model

Model Capabilities

Image understanding

Text generation

Cross-modal reasoning

Visual question answering

Use Cases

Visual question answering

Image content description

Generate a detailed textual description based on the input image

Visual reasoning

Perform logical reasoning and answer questions based on the image content

Education

Educational assistance

Help students understand complex charts and visual materials

Property	Details
Pipeline Tag	image-text-to-text
Library Name	transformers
Base Model	Qwen/Qwen2-VL-7B-Instruct
Training Datasets	HuanjinYao/Mulberry-SFT

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R1 VL 7B

Model Overview

Model Features

Model Capabilities

Use Cases

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📄 Paper

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🧠 Base Model

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