Instructions to use RunDiffusion/RunDiffusion-XL-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RunDiffusion/RunDiffusion-XL-Beta with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RunDiffusion/RunDiffusion-XL-Beta", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 65f5e485313f0718d12e2bc8e9ebeb2a7cc2edbb11e8645b998721a68b8a09b2
- Size of remote file:
- 5.14 GB
- SHA256:
- a3ffb245cb9786e43b48a7aba014dbbea67148b618dbb82485a99a8d26da0a13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.