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("rorito/smog")
prompt = "selfie photo of a man with brown hair and a blonde woman hugging on the beach with clouds in the sky, romanticism, amateur iphone photo, socmed, <lora:Zphyr_FLUX_Photorealistic_LoRA:0.4> <lora:socmed_v2:0.65> <lora:photooo-000001:0.5> <lora:iphone-dev-7:0.65> <lora:amateurphoto-6version:0.65>"
image = pipe(prompt).images[0]socmed
- Prompt
- selfie photo of a man with brown hair and a blonde woman hugging on the beach with clouds in the sky, romanticism, amateur iphone photo, socmed, <lora:Zphyr_FLUX_Photorealistic_LoRA:0.4> <lora:socmed_v2:0.65> <lora:photooo-000001:0.5> <lora:iphone-dev-7:0.65> <lora:amateurphoto-6version:0.65>
Trigger words
You should use socmed 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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Base model
black-forest-labs/FLUX.1-dev