Instructions to use ModelsLab/blipdiffusion-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ModelsLab/blipdiffusion-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ModelsLab/blipdiffusion-controlnet", 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:
- d04121d3e8f24fcd55e42ff7c53467a9f37ce15563738550e43f5ce529d4e898
- Size of remote file:
- 1.98 GB
- SHA256:
- 2beb7ccb198585f2da2e7e8699aaea821274eeb946baf82d2b181139dedd5b2e
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