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("busetolunay/building_flux_lora_v3")
prompt = "[trigger] coffe shopbuilding "
image = pipe(prompt).images[0]building_flux_lora_v3
Model trained with AI Toolkit by Ostris
- Prompt
- [trigger] coffe shopbuilding
- Prompt
- [trigger] summerhouse building with a front porch'
- Prompt
- [trigger] glass greenhouse
- Prompt
- [trigger] art museum building
- Prompt
- [trigger] egyptian themed house
- Prompt
- [trigger] egyptian pyramid
- Prompt
- [trigger] bungalow
- Prompt
- [trigger] church
- Prompt
- [trigger] courthouse building
- Prompt
- [trigger] barn
- Prompt
- [trigger] library building
- Prompt
- [trigger] lighthouse
- Prompt
- [trigger] tent
- Prompt
- [trigger] cottage house
- Prompt
- [trigger] doghouse
- Prompt
- [trigger] treehouse
- Prompt
- [trigger] mansion building
- Prompt
- [trigger] waffle house building
- Prompt
- [trigger] halloween themed house
Trigger words
You should use a0ce to trigger the image generation.
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Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for busetolunay/building_flux_lora_v3
Base model
black-forest-labs/FLUX.1-dev