FLUX

by Black Forest Labs: https://blackforestlabs.ai. Documentation for our API can be found here: docs.bfl.ml.

This repo contains minimal inference code to run image generation & editing with our Flux models.

Local installation

cd $HOME && git clone https://github.com/black-forest-labs/flux
cd $HOME/flux
python3.10 -m venv .venv
source .venv/bin/activate
pip install -e ".[all]"

Local installation with TensorRT support

If you would like to install the repository with TensorRT support, you currently need to install a PyTorch image from NVIDIA instead. First install enroot, next follow the steps below:

cd $HOME && git clone https://github.com/black-forest-labs/flux
enroot import 'docker://$oauthtoken@nvcr.io#nvidia/pytorch:25.01-py3'
enroot create -n pti2501 nvidia+pytorch+25.01-py3.sqsh
enroot start --rw -m ${PWD}/flux:/workspace/flux -r pti2501
cd flux
pip install -e ".[tensorrt]" --extra-index-url https://pypi.nvidia.com

Models

We are offering an extensive suite of models. For more information about the invidual models, please refer to the link under Usage.

Name	Usage	HuggingFace repo	License
FLUX.1 [schnell]	Text to Image	https://huggingface.co/black-forest-labs/FLUX.1-schnell	apache-2.0
FLUX.1 [dev]	Text to Image	https://huggingface.co/black-forest-labs/FLUX.1-dev	FLUX.1-dev Non-Commercial License
FLUX.1 Fill [dev]	In/Out-painting	https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev	FLUX.1-dev Non-Commercial License
FLUX.1 Canny [dev]	Structural Conditioning	https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev	FLUX.1-dev Non-Commercial License
FLUX.1 Depth [dev]	Structural Conditioning	https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev	FLUX.1-dev Non-Commercial License
FLUX.1 Canny [dev] LoRA	Structural Conditioning	https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev-lora	FLUX.1-dev Non-Commercial License
FLUX.1 Depth [dev] LoRA	Structural Conditioning	https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev-lora	FLUX.1-dev Non-Commercial License
FLUX.1 Redux [dev]	Image variation	https://huggingface.co/black-forest-labs/FLUX.1-Redux-dev	FLUX.1-dev Non-Commercial License
FLUX.1 [pro]	Text to Image	Available in our API.
FLUX1.1 [pro]	Text to Image	Available in our API.
FLUX1.1 [pro] Ultra/raw	Text to Image	Available in our API.
FLUX.1 Fill [pro]	In/Out-painting	Available in our API.
FLUX.1 Canny [pro]	Structural Conditioning	Available in our API.
FLUX.1 Depth [pro]	Structural Conditioning	Available in our API.
FLUX1.1 Redux [pro]	Image variation	Available in our API.
FLUX1.1 Redux [pro] Ultra	Image variation	Available in our API.

The weights of the autoencoder are also released under apache-2.0 and can be found in the HuggingFace repos above.

API usage

Our API offers access to our models. It is documented here: docs.bfl.ml.

In this repository we also offer an easy python interface. To use this, you first need to register with the API on api.bfl.ml, and create a new API key.

To use the API key either run export BFL_API_KEY=<your_key_here> or provide it via the api_key=<your_key_here> parameter. It is also expected that you have installed the package as above.

Usage from python:

from flux.api import ImageRequest

# this will create an api request directly but not block until the generation is finished
request = ImageRequest("A beautiful beach", name="flux.1.1-pro")
# or: request = ImageRequest("A beautiful beach", name="flux.1.1-pro", api_key="your_key_here")

# any of the following will block until the generation is finished
request.url
# -> https:<...>/sample.jpg
request.bytes
# -> b"..." bytes for the generated image
request.save("outputs/api.jpg")
# saves the sample to local storage
request.image
# -> a PIL image

Usage from the command line:

$ python -m flux.api --prompt="A beautiful beach" url
https:<...>/sample.jpg

# generate and save the result
$ python -m flux.api --prompt="A beautiful beach" save outputs/api

# open the image directly
$ python -m flux.api --prompt="A beautiful beach" image show

Citation

If you find the provided code or models useful for your research, consider citing them as:

@misc{flux2024,
    author={Black Forest Labs},
    title={FLUX},
    year={2024},
    howpublished={\url{https://github.com/black-forest-labs/flux}},
}