Instructions to use bumblebee-testing/tiny-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bumblebee-testing/tiny-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("bumblebee-testing/tiny-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:
- d92479bd3ce3037860eace069c36e11daca995a769d9b5c36dce5f35859031df
- Size of remote file:
- 2.81 MB
- SHA256:
- 94ce18d5dd1a9b75e6f82e1d23b7aee970781a0d2595a2e442ecc4b935b70313
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