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:
- f8254a1595c284559f62ec44071ad214e2c27429d27e62295b9861c29696183f
- Size of remote file:
- 1.39 GB
- SHA256:
- 497f2394e692a73a7a89efecec119c4083e17b8714fb67bdcc70df058079a3fb
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