FLUX.1 Dev LoRA AntiBlur

🚀 FLUX.1-dev-LoRA-AntiBlur

This is a functional LoRA trained on FLUX.1-dev for deep DoF (Anti-Blur🔥). It was trained by Vadim_Fedenko on Shakker AI. Although it may not be fancy, it works effectively.

✨ Features

• This LoRA has very little damage to image quality while enhancing the depth of field.
• It can be used together with other components, such as ControlNet. It is regarded as a basic functional LoRA.

📋 Comparison

The following example shows a simple comparison with FLUX.1-dev under the same parameter setting.

📝 Trigger words

The trigger word is not required. The recommended scale is 1.0 to 1.5 in diffusers.

💻 Usage Examples

Basic Usage

import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-AntiBlur", weight_name="FLUX-dev-lora-AntiBlur.safetensors")
pipe.fuse_lora(lora_scale=1.5)
pipe.to("cuda")

prompt = "a young college student, walking on the street, campus background, photography"

image = pipe(prompt, 
             num_inference_steps=24, 
             guidance_scale=3.5,
             width=768, height=1024,
            ).images[0]
image.save(f"example.png")

🌐 Online Inference

You can also run this model at Shakker AI, where we provide an online interface to generate images.

📄 License

This model is trained by our copyrighted users Vadim_Fedenko. We release this model under permissions. The model follows flux-1-dev-non-commercial-license.