Instructions to use Jinstudio/stable-diffusion-2-depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jinstudio/stable-diffusion-2-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("Jinstudio/stable-diffusion-2-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
Download depth_estimator/pytorch_model.bin from Jinstudio/stable-diffusion-2-depth: direct link, hf CLI and curl.
- Browser
- Download file 490 MB
-
https://huggingface.co/Jinstudio/stable-diffusion-2-depth/resolve/main/depth_estimator/pytorch_model.bin
- Command line
-
hf download hf://Jinstudio/stable-diffusion-2-depth/depth_estimator/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jinstudio/stable-diffusion-2-depth/resolve/main/depth_estimator/pytorch_model.bin
490 MB
- Xet hash:
- 38ed955c8797676ee30b8643e6c2e5c65a78baefe5a0a5408eeb2ce450c35633
- Size of remote file:
- 490 MB
- SHA256:
- b6c4d44f9d96ca3fa76dd3bbb153989a60b4ad5526559f3c598562a368d687ec
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