tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- image-generation
- flux
- safetensors
widget:
- text: >-
a young college student, walking on the street, campus background,
photography
output:
url: images/2f82e6b1e5969d70a9044c19975bcdcca06b0f251d14f9c2c6095fa6.jpg
- text: a young woman, New York City
output:
url: images/340c1ae6709f56f3d8176848653dcade93d2b5b8ade662da167ef818.jpg
- text: >-
happy stunning girl with long dark hair, wearing blue clothes, playing
guitar, a beautiful field of flowers, colorful flowers everywhere, hills
in the background
output:
url: images/ec9a40eed46e8d17d3db1560a6543c6e6be9ebe1e41ecd5d137c01e0.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co./black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
FLUX.1-dev-LoRA-AntiBlur
This is a functional LoRA trained on FLUX.1-dev for deep DoF (Anti-Blur🔥) by Vadim_Fedenko on Shakker AI. It may not be fancy, but it works.
Comparison
The following example shows a simple comparison with FLUX.1-dev under the same parameter setting.
It is worth noting that this LoRA has very little damage to image quality while enhancing the depth of field, and can be used together with other components, such as ControlNet. We regard it as a basic functional LoRA.
Trigger words
The trigger word is not required. The recommended scale is 1.0 to 1.5 in diffusers.
Inference
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.
Acknowledgements
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.