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README
Apache-2.0

SolidUI

一句话生成任何图形

github stars github contributors page views hugging face spaces solidui website producthunt discord gitee us on slack



English | 中文

介绍

AI生成图形模型

核心特点

  • 极简流程,简洁设计
  • 多种2D图例
  • 多种3D图例
  • 多种3D场景
  • 支持多种数据源
  • 支持Huggingface space
  • 支持插件机器人
  • 支持SolidUI模型
  • 支持大模型接入
  • 容器化部署

快速开始

快速开始

这是什么?

随着文本生成图像的语言模型兴起,SolidUI想帮人们快速构建可视化工具,可视化内容包括2D,3D,3D场景,从而快速构三维数据演示场景。SolidUI 是一个创新的项目,旨在将自然语言处理(NLP)与计算机图形学相结合,实现文生图功能。通过构建自研的文生图语言模型,SolidUI 利用 RLHF (Reinforcement Learning Human Feedback) 流程实现从文本描述到图形生成的过程。

自研文生图语言模型

SolidUI 的文生图语言模型是一个深度学习模型,可以将用户输入的自然语言描述转换为具体的图形表示。这个模型在大量文本和图形数据上进行训练,学习到从文本到图形的映射关系。为了实现这一目标,SolidUI 的自研文生图语言模型具有以下特点:

  • 结合 NLP 和计算机图形学,实现从文本描述到图形生成的过程
  • 可处理多种类型的图形,如 2D、3D 和场景等
  • 模型训练过程涉及大量的文本和图形数据,以确保生成的图形质量和准确性

RLHF 流程

SolidUI 使用 RLHF (Reinforcement Learning Human Feedback) 流程来优化文生图语言模型的性能。该流程利用人类反馈来指导模型的学习过程,从而使模型能够更好地满足用户需求。RLHF 流程的主要步骤包括:

  • 收集反馈:用户对生成的图形进行评价,提供关于图形质量和准确性的反馈。
  • 更新模型:根据收集到的反馈,使用强化学习算法对模型进行更新,以提高生成图形的质量和准确性。
  • 迭代优化:重复收集反馈和更新模型的过程,直到模型性能达到满意的水平。

通过这一流程,SolidUI 的文生图语言模型能够不断地从用户反馈中学习和进步,生成更高质量和准确性的图形。

文档

SolidUI 的完整文档列表,请参见 SolidUI-Website

贡献

我们非常欢迎和期待更多的贡献者参与共建 SolidUI, 不论是代码、文档,或是其他能够帮助到社区的贡献形式。

联系我们

  • 对 SolidUI 的任何问题和建议,可以提交 issue,以便跟踪处理和经验沉淀共享
  • twitter
  • youtube
  • bilibili (in Chinese)
  • discord
  • 可以扫描下面的二维码,加入我们的微信群,以获得更快速的响应 (in Chinese)

SolidUI1

  • 微信公众号 (in Chinese)

SolidUI2

谁在使用 SolidUI

我们创建了一个 issue [Who is Using SolidUI] 以便用户反馈和记录谁在使用 SolidUI.

Contributors

Thanks to everyone who contributed PR~ 🎉🎉🎉

感谢与赞助

我们非常感谢您对我们项目和开发工作的支持和认可。在开源软件开发过程中,我们深知用户和社区的反馈与支持是至关重要的。我们的项目已经提供了 README 和 Issue 系统,方便用户进行部署和解决问题,同时也有助于提升项目的活跃度。我们会优先关注 issue 中提出的问题。

如果您对于社区有兴趣,欢迎参与(代码,文档,使用),欢迎任何形式参与。

如果您觉得 SolidUI 项目对您有价值,并愿意支持我们的开发工作,请为项目点个小星星或赞助我们

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