Instructions to use tensorart/SD3.5M-Controlnet-Depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tensorart/SD3.5M-Controlnet-Depth 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-Depth", 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
- Draw Things
- DiffusionBee
- Xet hash:
- eb6a4c759f10f94f0c42d8093f78858bbb633d6b65cb6f153e591ed991263154
- Size of remote file:
- 4.93 GB
- SHA256:
- f768adb86fa5585afd4fc9a301317d703c69921630278e1f8095364c6f71a306
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