# flux **Repository Path**: chandlersong/flux ## Basic Information - **Project Name**: flux - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-06-05 - **Last Updated**: 2025-06-05 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # FLUX by Black Forest Labs: https://blackforestlabs.ai. Documentation for our API can be found here: [docs.bfl.ml](https://docs.bfl.ml/). ![grid](assets/grid.jpg) This repo contains minimal inference code to run image generation & editing with our Flux models. ## Local installation ```bash 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](https://github.com/NVIDIA/TensorRT) support, you currently need to install a PyTorch image from NVIDIA instead. First install [enroot](https://github.com/NVIDIA/enroot), next follow the steps below: ```bash 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](docs/text-to-image.md) | https://huggingface.co/black-forest-labs/FLUX.1-schnell | [apache-2.0](model_licenses/LICENSE-FLUX1-schnell) | | `FLUX.1 [dev]` | [Text to Image](docs/text-to-image.md) | https://huggingface.co/black-forest-labs/FLUX.1-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Fill [dev]` | [In/Out-painting](docs/fill.md) | https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Canny [dev]` | [Structural Conditioning](docs/structural-conditioning.md) | https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Depth [dev]` | [Structural Conditioning](docs/structural-conditioning.md) | https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Canny [dev] LoRA` | [Structural Conditioning](docs/structural-conditioning.md) | https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev-lora | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Depth [dev] LoRA` | [Structural Conditioning](docs/structural-conditioning.md) | https://huggingface.co/black-forest-labs/FLUX.1-Depth-dev-lora | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 Redux [dev]` | [Image variation](docs/image-variation.md) | https://huggingface.co/black-forest-labs/FLUX.1-Redux-dev | [FLUX.1-dev Non-Commercial License](model_licenses/LICENSE-FLUX1-dev) | | `FLUX.1 [pro]` | [Text to Image](docs/text-to-image.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX1.1 [pro]` | [Text to Image](docs/text-to-image.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX1.1 [pro] Ultra/raw` | [Text to Image](docs/text-to-image.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX.1 Fill [pro]` | [In/Out-painting](docs/fill.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX.1 Canny [pro]` | [Structural Conditioning](docs/structural-conditioning.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX.1 Depth [pro]` | [Structural Conditioning](docs/structural-conditioning.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX1.1 Redux [pro]` | [Image variation](docs/image-variation.md) | [Available in our API.](https://docs.bfl.ml/) | | | `FLUX1.1 Redux [pro] Ultra` | [Image variation](docs/image-variation.md) | [Available in our API.](https://docs.bfl.ml/) | | The weights of the autoencoder are also released under [apache-2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) 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](https://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](https://api.bfl.ml/), and create a new API key. To use the API key either run `export BFL_API_KEY=` or provide it via the `api_key=` parameter. It is also expected that you have installed the package as above. Usage from python: ```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: ```bash $ 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: ```bib @misc{flux2024, author={Black Forest Labs}, title={FLUX}, year={2024}, howpublished={\url{https://github.com/black-forest-labs/flux}}, } ```