Instructions to use DmitryMLC/yk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DmitryMLC/yk with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DmitryMLC/yk", 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:
- 12609b9801ba9c8041f5f76e1c3b1c128384f9880507f16ff1da2519bc49920d
- Size of remote file:
- 492 MB
- SHA256:
- b33bc3de969612dca6baf9227944db5d518b851ee97f98dd6b9541f7ce64b6eb
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