Install and Run Mochi 1 on Ubuntu: A Complete Guide
Learn how to install Mochi 1 on Ubuntu for AI-powered text-to-video generation. Step-by-step guide with optimization tips, troubleshooting, and advanced features.
Mochi 1 is an open-source AI video generation model developed by Genmo that transforms text prompts into dynamic videos. Whether you’re a content creator, marketer, or developer, this guide will help you install and optimize Mochi 1 on Ubuntu for seamless AI-driven video creation.
System Requirements
Ensure your Ubuntu system meets these specs:
| Component | Minimum Requirement | Recommended |
|---|---|---|
| OS | Ubuntu 20.04 LTS | Ubuntu 22.04 LTS |
| CPU | Intel i5 / AMD Ryzen 5 | Intel i7 / AMD Ryzen 7 |
| RAM | 16 GB | 32 GB |
| GPU | NVIDIA GPU (8 GB VRAM) | NVIDIA RTX 3090 (24 GB VRAM) |
| Python | 3.8+ | 3.10+ |
Step-by-Step Installation
Step 1: Update Your System
To ensure all packages are up-to-date, run the following command in your terminal:
sudo apt update && sudo apt upgrade -y
Step 2: Install Required Packages
Install essential dependencies including Git, Python, and pip:
sudo apt install git python3 python3-pip -y
Step 3: Install CUDA and cuDNN (For NVIDIA GPUs)
To fully utilize your GPU, install CUDA and cuDNN:
- Install CUDA:
- Download it from NVIDIA CUDA Toolkit.
- Follow the installation instructions for Ubuntu.
- Install cuDNN:
- Get it from the NVIDIA Developer website.
- Extract the files and copy them to
/usr/local/cuda.
Step 4: Clone the Mochi Repository
Clone the Mochi GitHub repository and navigate into it:
git clone https://github.com/genmoai/mochi.git
cd mochi
Step 5: Install Python Dependencies
Inside the mochi directory, install all required Python packages:
pip install -r requirements.txt
Step 6: Configure Environment Variables
Set up CUDA environment variables by adding the following lines to your ~/.bashrc file:
export PATH=/usr/local/cuda/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
Apply the changes:
source ~/.bashrc
Step 7: Run Mochi
To start video generation using Mochi, use the following command:
python run_mochi.py --text "Your text prompt here"
Running Your First Video Generation
Generate a video from a text prompt:
python run_mochi.py --text "A futuristic cityscape at sunset" --output video.mp4
Example Output: A 5-second video at 24 FPS saved as video.mp4.
Optimizing Performance
GPU Memory Management
- Reduce Batch Size: For 8 GB VRAM, use
--batch_size 1. - Adjust Resolution: Lower
--heightand--width(default: 512x512).
Mixed Precision Training
Add --fp16 to use 16-bit precision for faster inference:
python run_mochi.py --text "A forest waterfall" --fp16
Monitor GPU Usage
watch -n 1 nvidia-smi
Troubleshooting Common Issues
| Issue | Solution |
|---|---|
| CUDA Out of Memory | Reduce --batch_size or resolution. |
| Dependency Conflicts | Use a virtual environment. |
| cuDNN Not Detected | Verify CUDA/cuDNN paths in ~/.bashrc. |
Advanced Features
1. Custom Checkpoints
Download community-trained models from Mochi Community Hub and load them with:
python run_mochi.py --checkpoint custom_model.ckpt
2. ComfyUI Integration
Use the visual interface for workflow management:
- Install ComfyUI.
- Import Mochi 1 nodes for drag-and-drop video generation.
Conclusion
Mochi 1 on Ubuntu unlocks limitless possibilities for AI video generation. By following this guide, you’ve set up a robust environment for creating videos from text prompts, optimized performance, and explored advanced features. Stay updated with the Mochi GitHub repo for the latest enhancements!