Instructions to use johnberg/resedit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use johnberg/resedit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("johnberg/resedit", 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
- Xet hash:
- f9c1a25492b0f113a62b3932baac891cda328105382415319a2c2ba02085f65b
- Size of remote file:
- 4.56 GB
- SHA256:
- 4271fa9ad53fd3959f0b996787c5e7e9f36763f7d7af74e9ec3d6b292a287b6c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.