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:
- 9d4b63a840e927cb3d622fa3a9a4b2c76b61452cbacdff4c99c86a22889c3f0b
- Size of remote file:
- 1.46 GB
- SHA256:
- 8baa60ac11b88a512540dd64164fecda3d767a971ff738289d59414f75be62d6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.