Instructions to use InstantX/FLUX.1-dev-Controlnet-Union with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/FLUX.1-dev-Controlnet-Union with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/FLUX.1-dev-Controlnet-Union", 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.safetensors from InstantX/FLUX.1-dev-Controlnet-Union: direct link, hf CLI and curl.
- Browser
- Download file 6.6 GB
-
https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://InstantX/FLUX.1-dev-Controlnet-Union/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/InstantX/FLUX.1-dev-Controlnet-Union/resolve/main/diffusion_pytorch_model.safetensors
6.6 GB
- Xet hash:
- 0ec7deeff0e8d407744dbc96ce867b842ff11d51cc0c6132a3bd271091f041e1
- Size of remote file:
- 6.6 GB
- SHA256:
- 2cd23f9da9f2f24d75ded22c0c2596782312aa0b88e05076b4b8621a0b1fa9d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.