Instructions to use krnl/control_v11p_sd15_canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krnl/control_v11p_sd15_canny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krnl/control_v11p_sd15_canny", 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
Download diffusion_pytorch_model.bin from krnl/control_v11p_sd15_canny: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/krnl/control_v11p_sd15_canny/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://krnl/control_v11p_sd15_canny/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/krnl/control_v11p_sd15_canny/resolve/main/diffusion_pytorch_model.bin
1.45 GB
- Xet hash:
- 9cf3365907607ccbd6f728691fda1fe4fe7a1cf1fee6e53b795724076b0687f8
- Size of remote file:
- 1.45 GB
- SHA256:
- 62364453cb4230f0e94669b4d36d723c292622268c3d5e30ed4aff128c7509f1
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