Instructions to use MAVS/urkov1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MAVS/urkov1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MAVS/urkov1", 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:
- b6e1d598d6e2bbe7664566f2b002f27ac333f10f944aab6e3e356d7195c817cd
- Size of remote file:
- 492 MB
- SHA256:
- e4bbb9f3a28e2e1619476021f115d424f71f88e19ab62454e8b0fa5ed048fc4c
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