---
title: VisionReward-Image-bf16
canonical_url: "https://www.modelscope.cn/models/ZhipuAI/VisionReward-Image-bf16"
md_url: "https://www.modelscope.cn/models/ZhipuAI/VisionReward-Image-bf16.md"
repository: ZhipuAI/VisionReward-Image-bf16
last_updated: 2025-02-13
downloads: 414
stars: 0
---

# VisionReward-Image-bf16

> VisionReward-Image-bf16 - ZhipuAI 在 ModelScope 开源的模型。VisionReward-Image Introduction We present VisionReward, a general strategy to aligning visual generation models——both image and video generation——with human preferences through a fine-grainedand…

- **Repository**: ZhipuAI/VisionReward-Image-bf16
- **Downloads**: 414
- **Stars**: 0
- **Last updated**: 2025-02-13

Source: https://www.modelscope.cn/models/ZhipuAI/VisionReward-Image-bf16

---

# VisionReward-Image

## Introduction
We present VisionReward, a general strategy to aligning visual generation models——both image and video generation——with human preferences through a fine-grainedand multi-dimensional framework. We decompose human preferences in images and videos into multiple dimensions,each represented by a series of judgment questions, linearly weighted and summed to an interpretable and accuratescore. To address the challenges of video quality assess-ment, we systematically analyze various dynamic features of videos, which helps VisionReward surpass VideoScore by 17.2% and achieve top performance for video preference prediction.
Here, we present the model of VisionReward-Image.

## Merging and Extracting Checkpoint Files
Use the following command to merge the split files into a single `.tar` file and then extract it into the specified directory:

```sh
cat ckpts/split_part_* > ckpts/visionreward_image.tar
tar -xvf ckpts/visionreward_image.tar
```

## Using this model
You can quickly install the Python package dependencies and run model inference in our [github](https://github.com/THUDM/VisionReward).
> This model utilizes bf16 precision parameters and requires the use of the sat (SwissArmyTransformer) library for invocation. For the fp32 version of the model, please refer to the following link: [https://huggingface.co/THUDM/VisionReward-Image-bf16](https://huggingface.co/THUDM/VisionReward-Image-bf16)