Instructions to use genmo/mochi-1-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use genmo/mochi-1-preview with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("genmo/mochi-1-preview", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Genmo
How to use genmo/mochi-1-preview with Genmo:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Inference
- Notebooks
- Google Colab
- Kaggle
Update README with installation, download, running instructions and model details
#21
by thesab - opened
This pull request updates the README to improve readability, formatting, and provides additional instructions. Changes include:
- Properly formatted installation steps using uv, including setuptools and flash attention.
- Structured and clear instructions for downloading model weights with direct links.
- Clear and formatted instructions for running the Gradio UI and generating videos from the CLI.
- Detailed section on running with Diffusers, including sub-section for using a lower precision variant.
- Enhanced readability and structure in the Model Architecture section.
- Detailed hardware requirements and safety considerations.
- Expanded limitations section.
- Properly formatted BibTeX citation.
Amazing!. Thanks.
I'm going to manually update the README, since I don't know how to fix merge conflicts in huggingface.
paras-genmo changed pull request status to closed


