Instructions to use enryu43/anifusion_sd_unet_768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use enryu43/anifusion_sd_unet_768 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("enryu43/anifusion_sd_unet_768", 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:
- d4d4a40fbe876edc6cb4d0286c28f6a3fd2731e29eaa87ec81b53d84d40e4e2b
- Size of remote file:
- 4.4 GB
- SHA256:
- c6c179feab60010ae0f789ee9fbaf9454ad1470c4297ecbe3d309dfcf6536402
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.