Instructions to use raisahil/scunge-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use raisahil/scunge-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("raisahil/scunge-model", 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:
- 4a040cbd465727c92ac1884b168843e712caf4deee43e97ad7a0614c170c5990
- Size of remote file:
- 2.13 MB
- SHA256:
- b19da6052f01a3b115ac3315ef5db1b7dcdb58091879c0dfe3895a7765a491ac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.