Instructions to use jasperai/Flux.1-dev-Controlnet-Depth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jasperai/Flux.1-dev-Controlnet-Depth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jasperai/Flux.1-dev-Controlnet-Depth", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download diffusion_pytorch_model.safetensors from jasperai/Flux.1-dev-Controlnet-Depth: direct link, hf CLI and curl.
- Browser
- Download file 3.58 GB
-
https://huggingface.co/jasperai/Flux.1-dev-Controlnet-Depth/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://jasperai/Flux.1-dev-Controlnet-Depth/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/jasperai/Flux.1-dev-Controlnet-Depth/resolve/main/diffusion_pytorch_model.safetensors
3.58 GB
- Xet hash:
- 458cb5c1e8f98c0e35ab10608469f86d3043625c97fe606e7a4995958aa8425e
- Size of remote file:
- 3.58 GB
- SHA256:
- cc0f727200656f5cbadd4e7de805fbe072a07955993e1a9415b052eb629c7e5d
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