by Black Forest Labs: https://blackforestlabs.ai. Documentation for our API can be found here: docs.bfl.ml.
This fork of Flux Fill is an illustration on how one can set up on an existing model some fast and properly working CPU offloading with very few changes in the core model.
For more information on how to use the mmpg module, please go to: https://github.com/deepbeepmeep/mmgp
Beside the support for 24 GB VRAM GPU with fast generation of images, I did a few improvements to the Flux Fill tool:
- bug fixing
- progression bar
- automatic resizing of large images
- user interface streamlined
Once the installation is done (see instructions below), run the Flux Fill tool with the command:
streamlit run demo_st_fill.pyA minimum of 48 GB in your RAM is needed to run this tool.
If you have more than 64 GB RAM you can set the option pinInRAM = True on line 85 of file demo_st_fill.py
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]"We are offering an extensive suite of models. For more information about the invidual models, please refer to the link under Usage.
The weights of the autoencoder are also released under apache-2.0 and can be found in the HuggingFace repos above.
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 imageUsage 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