import replicate

input = {
    "prompt": "gh_comunicaciones_serie_mototrbo_dep_500e_6_20250411_1634",
    "lora_weights": "https://huggingface.co/BilateralBusiness/gh_comunicaciones_serie_mototrbo_dep_500e_6_20250411_1634/resolve/main/lora.safetensors"
}

output = replicate.run(
    "black-forest-labs/flux-dev-lora",
    input=input
)
for index, item in enumerate(output):
    with open(f"output_{index}.webp", "wb") as file:
        file.write(item.read())

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('BilateralBusiness/gh_comunicaciones_serie_mototrbo_dep_500e_6_20250411_1634', weight_name='lora.safetensors')
image = pipeline('gh_comunicaciones_serie_mototrbo_dep_500e_6_20250411_1634').images[0]

For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers

Training details

Steps: 1000
Learning rate: 0.0004
LoRA rank: 16

Contribute your own examples

You can use the community tab to add images that show off what you’ve made with this LoRA.