Models
FLUX.1 Fill introduces advanced inpainting and outpainting capabilities. It allows for seamless edits that integrate naturally with existing images.
| Name | HuggingFace repo | License | sha256sum |
|---|---|---|---|
FLUX.1 Fill [dev] |
https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev | FLUX.1-dev Non-Commercial License | 03e289f530df51d014f48e675a9ffa2141bc003259bf5f25d75b957e920a41ca |
FLUX.1 Fill [pro] |
Only available in our API. |
Examples
Open-weights usage
The weights will be downloaded automatically from HuggingFace once you start one of the demos. To download FLUX.1 Fill [dev], you will need to be logged in, see here. Alternatively, if you have downloaded the model weights manually from here, you can specify the downloaded paths via environment variables:
export FLUX_DEV_FILL=<path_to_flux_dev_fill_sft_file>
export AE=<path_to_ae_sft_file>
For interactive sampling run
python -m src.flux.cli_fill --loop
Or to generate a single sample run
python -m src.flux.cli_fill \
--img_cond_path <path_to_input_image> \
--img_cond_mask <path_to_input_mask>
The input_mask should be an image of the same size as the conditioning image that only contains black and white pixels; see an example mask for this image.
We also provide an interactive streamlit demo. The demo can be run via
streamlit run demo_st_fill.py