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
- Draw Things
- DiffusionBee
- Xet hash:
- c393d2d8772efee17dc53c4e52d9e9b91e6552be5d0ea07221a36541ca3a18fb
- Size of remote file:
- 170 MB
- SHA256:
- 7074b87c3414a66163dcf067d584c06a141c76e1c48930bdead30f8a7bb58fb4
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