Instructions to use tensorart/SD3.5M-Controlnet-Canny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tensorart/SD3.5M-Controlnet-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("tensorart/SD3.5M-Controlnet-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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 95d6d156b988870d8c8bd96cf2e8a7cd9647c2718bb12a98f7af6895f94f8173
- Size of remote file:
- 4.93 GB
- SHA256:
- 60f6eeaf265ba3336705ecd6dcd8170985fa577bc5f04fd7649aca06f139634a
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