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
Update README.md
Browse files
README.md
CHANGED
|
@@ -92,7 +92,7 @@ from diffusers.utils import load_image
|
|
| 92 |
from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
|
| 93 |
|
| 94 |
base_model = 'black-forest-labs/FLUX.1-dev'
|
| 95 |
-
controlnet_model_union = '
|
| 96 |
|
| 97 |
controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
|
| 98 |
controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
|
|
|
|
| 92 |
from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
|
| 93 |
|
| 94 |
base_model = 'black-forest-labs/FLUX.1-dev'
|
| 95 |
+
controlnet_model_union = 'InstantX/FLUX.1-dev-Controlnet-Union'
|
| 96 |
|
| 97 |
controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
|
| 98 |
controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
|