README.md

metadata

language:
  - en
license: other
license_name: flux-1-dev-non-commercial-license
license_link: LICENSE.md
extra_gated_prompt: >-
  By clicking "Agree", you agree to the [FluxDev Non-Commercial License
  Agreement](https://huggingface.co./black-forest-labs/FLUX.1-Depth-dev/blob/main/LICENSE.md)
  and acknowledge the [Acceptable Use
  Policy](https://huggingface.co./black-forest-labs/FLUX.1-Depth-dev/blob/main/POLICY.md).
tags:
  - image-generation
  - flux
  - diffusion-single-file

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.

Usage

We provide a reference implementation of FLUX.1 Redux [dev], as well as sampling code, in a dedicated github repository.

API Endpoints

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.

Diffusers

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

---

Limitations

• This model is not intended or able to provide factual information.
• As a statistical model this checkpoint might amplify existing societal biases.
• The model may fail to generate output that matches the prompts.
• Outputs are heavily influenced by the input image.

Out-of-Scope Use

The model and its derivatives may not be used

• In any way that violates any applicable national, federal, state, local or international law or regulation.
• For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; including but not limited to the solicitation, creation, acquisition, or dissemination of child exploitative content.
• To generate or disseminate verifiably false information and/or content with the purpose of harming others.
• To generate or disseminate personal identifiable information that can be used to harm an individual.
• To harass, abuse, threaten, stalk, or bully individuals or groups of individuals.
• To create non-consensual nudity or illegal pornographic content.
• For fully automated decision making that adversely impacts an individual's legal rights or otherwise creates or modifies a binding, enforceable obligation.
• Generating or facilitating large-scale disinformation campaigns.

License

This model falls under the FLUX.1 [dev] Non-Commercial License.