Instructions to use igorshmel/arisha_cool_clean_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use igorshmel/arisha_cool_clean_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("igorshmel/arisha_cool_clean_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
- Draw Things
- DiffusionBee
- Xet hash:
- f80a419af4889838903bdd303bea1eefebabf170681de24e86033522bfc62577
- Size of remote file:
- 492 MB
- SHA256:
- 15bff43a1d906ca4ff823893def69138b7e020da23760f1d64242348d37e1d7a
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