FLUX.1 Redux [dev] is an image variation generation adapter for all FLUX.1 base models. It enables users to refine images with slight variations and supports text-based restyling via API. Integrated with FLUX1.1 [pro] Ultra, it allows for high-quality 4-megapixel outputs. The model can be used with Diffusers in Python for efficient image generation. While powerful, it has ethical and factual limitations and is governed by a non-commercial license.
FLUX.1 Redux [dev] is an image variation generation adapter for all FLUX.1 base models. It enables users to refine images with slight variations and supports text-based restyling via API. Integrated with FLUX1.1 [pro] Ultra, it allows for high-quality 4-megapixel outputs. The model can be used with Diffusers in Python for efficient image generation. While powerful, it has ethical and factual limitations and is governed by a non-commercial license.
Please upload an image file
Num Images
number of images to generate (Default: 1, 1 ≤ num_images ≤ 4)
Num Inference Steps
number of denoising steps (Default: 25, 1 ≤ num_inference_steps ≤ 50)
Guidance Scale
classifier-free guidance, higher means follow prompt more closely (Default: 7.5, 0 ≤ guidance_scale ≤ 20)
image width in px (Default: 1024, 128 ≤ width ≤ 2048)
image height in px (Default: 1024, 128 ≤ height ≤ 2048)
random seed, empty means random (Default: empty, 0 ≤ seed < 18446744073709552000)
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FLUX.1 Redux [dev] is an adapter for all FLUX.1 base models for image variation generation. Given an input image, FLUX.1 Redux can reproduce the image with slight variation, allowing to refine a given image. It naturally integrates into more complex workflows unlocking image restyling. Restyling via text is also available through our API by providing an image plus a language prompt. For more information, please read our blog post.
We provide a reference implementation of FLUX.1 Redux [dev]
, as well as sampling code, in a dedicated github repository.
FLUX.1 Redux [pro]
is available in our API bfl.ml. In addition to the [dev]
adapter, the API endpoint allows users to modify an image given a textual description.
The feature is supported in our latest model FLUX1.1 [pro] Ultra, allowing for combining input images and text prompts to create high-quality 4-megapixel outputs with flexible aspect ratios.
To use FLUX.1 Redux [pro]
with the 🧨 diffusers python library, first install or upgrade diffusers
pip install -U diffusers
Then you can use FluxPriorReduxPipeline
along with FluxPipeline
to generate images from images.
import torch
from diffusers import FluxPriorReduxPipeline, FluxPipeline
from diffusers.utils import load_image
pipe_prior_redux = FluxPriorReduxPipeline.from_pretrained("black-forest-labs/FLUX.1-Redux-dev", torch_dtype=torch.bfloat16).to("cuda")
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev" ,
text_encoder=None,
text_encoder_2=None,
torch_dtype=torch.bfloat16
).to("cuda")
image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/robot.png")
pipe_prior_output = pipe_prior_redux(image)
images = pipe(
guidance_scale=2.5,
num_inference_steps=50,
generator=torch.Generator("cpu").manual_seed(0),
**pipe_prior_output,
).images
images[0].save("flux-dev-redux.png")
To learn more check out the diffusers documentation
The model and its derivatives may not be used
This model falls under the FLUX.1 [dev]
Non-Commercial License.