Instructions to use SEVUNX/joydiffusion_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SEVUNX/joydiffusion_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("SEVUNX/joydiffusion_diffusers", torch_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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1528f9613f7ec6f46ec467bc3d995e60380e4a90923da77126ea813175476e82
- Size of remote file:
- 3.44 GB
- SHA256:
- 6701cbe6fb6ad484ae937c18668cd51bc735fab2c7ce2b786af8de39f51554e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.