Add README files and requirements

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# ComfyUI_RH_mammothmoda
ComfyUI custom nodes for MammothModa2 text-to-image generation.
## Features
- **Text-to-Image Generation**: High-quality image synthesis using MammothModa2
- **Optimized Performance**: INT8 quantization support for efficient inference
- **Flash Attention**: Enhanced speed with flash_attention_2
## Installation
### Via ComfyUI Manager (Recommended)
Search for "RunningHub Mammothmoda" in ComfyUI Manager and install.
### Manual Installation
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/HM-RunningHub/ComfyUI_RH_mammothmoda.git
cd ComfyUI_RH_mammothmoda
pip install -r requirements.txt
```
## Model Download
Download the MammothModa2-Preview model and place it in:
```
ComfyUI/models/MammothModa2-Preview/
```
Model source: Check official MammothModa2 repository for model weights.
## Usage
1. **Load Model**: Use "RunningHub Mammothmoda Loader" node
2. **Generate Image**: Connect to "RunningHub Mammothmoda T2I Sampler" node
3. **Configure**: Set prompt, size (width/height), steps, and guidance scales
4. **Run**: Execute workflow to generate images
## Nodes
- **RunningHub Mammothmoda Loader**: Loads the MammothModa2 model
- **RunningHub Mammothmoda T2I Sampler**: Generates images from text prompts
## Requirements
- CUDA-capable GPU (24GB VRAM recommended)
- PyTorch with CUDA support
- flash-attn package
## License
See LICENSE file for details.
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# ComfyUI_RH_mammothmoda
ComfyUI 自定义节点,用于 MammothModa2 文本生成图像。
## 功能特点
- **文本生成图像**:使用 MammothModa2 进行高质量图像合成
- **性能优化**:支持 INT8 量化实现高效推理
- **Flash Attention**:使用 flash_attention_2 加速
## 安装方法
### 通过 ComfyUI Manager 安装(推荐)
在 ComfyUI Manager 中搜索 "RunningHub Mammothmoda" 并安装。
### 手动安装
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/HM-RunningHub/ComfyUI_RH_mammothmoda.git
cd ComfyUI_RH_mammothmoda
pip install -r requirements.txt
```
## 模型下载
下载 MammothModa2-Preview 模型并放置到:
```
ComfyUI/models/MammothModa2-Preview/
```
模型来源:请查看 MammothModa2 官方仓库获取模型权重。
## 使用说明
1. **加载模型**:使用 "RunningHub Mammothmoda Loader" 节点
2. **生成图像**:连接到 "RunningHub Mammothmoda T2I Sampler" 节点
3. **配置参数**:设置提示词、尺寸(宽度/高度)、步数和引导比例
4. **运行**:执行工作流生成图像
## 节点说明
- **RunningHub Mammothmoda Loader**:加载 MammothModa2 模型
- **RunningHub Mammothmoda T2I Sampler**:从文本提示词生成图像
## 系统要求
- 支持 CUDA 的 GPU(推荐 24GB 显存)
- PyTorch(支持 CUDA)
- flash-attn 包
## 许可证
详见 LICENSE 文件。
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torch>=2.0.0
transformers>=4.40.0
optimum-quanto
qwen-vl-utils
flash-attn>=2.0.0
pillow
numpy