Instructions to use feizhengcong/mochi-1-preview-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use feizhengcong/mochi-1-preview-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("feizhengcong/mochi-1-preview-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cdad6522f06f8d4ff377e3c35b2e6499265aa455ca14b4d0b0f80544ed3836cb
- Size of remote file:
- 8.98 MB
- SHA256:
- 13d3d2e5fe3856538c45e00b08ae8dacfa85309a7cd206c49555b6b352e87798
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.