Instructions to use pilotj/custom-controlnet-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pilotj/custom-controlnet-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("pilotj/custom-controlnet-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
- Xet hash:
- b6e1d097a9fdadad0304701f1c43d2a7e13195349e8efa96258d9b6f7c93152d
- Size of remote file:
- 1.63 GB
- SHA256:
- d7ea28fb9c834e511b032593c9e8888960315c276363ffe9ac98f7ab13cb2747
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