Instructions to use Niggendar/RandomImpasto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Niggendar/RandomImpasto with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Niggendar/RandomImpasto", 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:
- 7def9c7d3f1d0a98fb0da7f6b0b8c564c7c7870216082ac748c5faa9de736985
- Size of remote file:
- 246 MB
- SHA256:
- 672d4cbd10aa8af7d2bf5ddb7c1b6e005295edf799f49b7d50d254c68f99d8db
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