Instructions to use svjack/canny-control-lora-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use svjack/canny-control-lora-zh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("svjack/canny-control-lora-zh", 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 svjack/canny-control-lora-zh: direct link, hf CLI and curl.
- Browser
- Download file 24.4 MB
-
https://huggingface.co/svjack/canny-control-lora-zh/resolve/main/diffusion_pytorch_model.bin
- Command line
-
hf download hf://svjack/canny-control-lora-zh/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/svjack/canny-control-lora-zh/resolve/main/diffusion_pytorch_model.bin
24.4 MB
- Xet hash:
- a2b7fd23d775224e59379520927aa99e97ad2852090c0eb8b32c2ad30f45215e
- Size of remote file:
- 24.4 MB
- SHA256:
- ce9d808b8e5a0605bc676aa2db378ec1aae8556197bac9b2804dd140e6910d4b
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