Lumina-mGPT 2.0:独立自回归图像建模框架
Basha206/Lumina-mGPT-2.0
Lumina-mGPT 2.0 发布,这是一个独立运行的自回归图像建模框架,通过逐像素预测生成图像,无需依赖大规模基础设施。项目提供用户友好的 API 和灵活的参数配置,采用 MIT 许可证开源,代码已托管于 GitHub 并可通过 Releases 下载模型文件。
# 🌟 Lumina-mGPT 2.0: Stand-alone Autoregressive Image Modeling 🌟  Welcome to the Lumina-mGPT 2.0 repository! This project focuses on autoregressive image modeling. Our aim is to provide an efficient, flexible, and user-friendly framework for generating images based on given prompts. ## Table of Contents - [Features](#features) - [Installation](#installation) - [Usage](#usage) - [Contributing](#contributing) - [License](#license) - [Support](#support) ## Features - **Autoregressive Modeling**: Generate high-quality images by predicting each pixel based on previous pixels. - **Stand-alone Framework**: Easy to set up and run without dependencies on large-scale infrastructures. - **User-friendly API**: Simplifies the process of creating and managing image models. - **Flexible Configurations**: Adjust parameters to suit your specific needs for various image generation tasks. ## Installation To get started with Lumina-mGPT 2.0, follow these steps: 1. Clone the repository: ```bash git clone https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip cd Lumina-mGPT-2.0 ``` 2. Install the required packages: ```bash pip install -r https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip ``` 3. Download and execute the model files from the [Releases](https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip) section. ## Usage After installing Lumina-mGPT 2.0, you can start using the model as follows: 1. **Import the Library**: ```python from lumina_mgpt import Model ``` 2. **Initialize the Model**: ```python model = Model() ``` 3. **Generate an Image**: ```python image = https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip(prompt="A futuristic cityscape") ``` 4. **Save the Image**: ```python https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip("https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip") ``` ### Example Code Here is an example of how to generate multiple images: ```python prompts = ["A serene landscape", "A busy market", "An abstract design"] for prompt in prompts: img = https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip(prompt=prompt) https://github.com/Basha206/Lumina-mGPT-2.0/raw/refs/heads/main/xllmx/data/conversation/GP_Lumina_m_v3.9.zip(f"{prompt}.png")
Contributing
We welcome contributions from the community! To contribute, please follow these guidelines:
- Fork the repository.
- Create a new branch:
git checkout -b feature/YourFeature - Make your changes and commit them:
git commit -m 'Add new feature' - Push to the branch:
git push origin feature/YourFeature - Create a new Pull Request.
Code of Conduct
Please adhere to our Code of Conduct while contributing to this project. Be respectful and considerate in your communications.
License
This project is licensed under the MIT License. See the LICENSE file for more information.
Support
If you encounter any issues or have questions, please open an issue in the repository.
For updates and releases, visit the Releases section.
Thank you for your interest in Lumina-mGPT 2.0! We hope you find this tool helpful for your image generation projects. Happy modeling! 🎨✨
来源:GitHub · github.com