Instructions to use Goodeat/controlnet-demosaicing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Goodeat/controlnet-demosaicing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Goodeat/controlnet-demosaicing", 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:
- 9e1a1719341f5615b280b59f8717c050241bad5c23c67100ba1c92824d33324a
- Size of remote file:
- 1.46 GB
- SHA256:
- 1cb6e81c0322c17af4fc7e225c372c3dc13bfdd3456a92b9946bec2ea3ca6020
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