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
Download vae_stats.json from genmo/mochi-1-preview: direct link, hf CLI and curl.
- Browser
- Download file 527 Bytes
-
https://huggingface.co/genmo/mochi-1-preview/resolve/refs%2Fpr%2F5/vae_stats.json
- Command line
-
hf download hf://genmo/mochi-1-preview@refs/pr/5/vae_stats.json
-
curl -L -o vae_stats.json https://huggingface.co/genmo/mochi-1-preview/resolve/refs%2Fpr%2F5/vae_stats.json
527 Bytes
| { | |
| "mean": [-0.06730895953510081, -0.038011381506090416, -0.07477820912866141, -0.05565264470995561, 0.012767231469026969, -0.04703542746246419, 0.043896967884726704, -0.09346305707025976, -0.09918314763016893, -0.008729793427399178, -0.011931556316503654, -0.0321993391887285], | |
| "std": [0.9263795028493863, 0.9248894543193766, 0.9393059390890617, 0.959253732819592, 0.8244560132752793, 0.917259975397747, 0.9294154431013696, 1.3720942357788521, 0.881393668867029, 0.9168315692124348, 0.9185249279345552, 0.9274757570805041] | |
| } | |