Instructions to use heboya8/controlnet-sd-2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use heboya8/controlnet-sd-2.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("heboya8/controlnet-sd-2.1", 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
- Xet hash:
- 4757315cd44d1c51a00ae0a8afb3c0226b434b1d10dcdd9a5f85c3fa3d7709ee
- Size of remote file:
- 741 MB
- SHA256:
- 26b7b36db9e8a50e7828e9eacaf6a45567e8f56f1c37aeeb94eadf2cf9217906
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