Instructions to use YucaCreative/flux_controlnet_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YucaCreative/flux_controlnet_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("YucaCreative/flux_controlnet_lora") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("YucaCreative/flux_controlnet_lora")
prompt = "-"
image = pipe(prompt).images[0]Flux Controlnet Lora

- Prompt
- -
Model description
Testing flux controlnet model.
Trigger words
You should use flux to trigger the image generation.
You should use controlnet to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for YucaCreative/flux_controlnet_lora
Base model
black-forest-labs/FLUX.1-dev