flux-fp8

Maintainer: Kijai - Last updated 9/4/2024

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Model overview

The flux-fp8 model is a float8 quantized version of the FLUX.1-dev and FLUX.1-schnell models developed by Black Forest Labs. These are 12 billion parameter rectified flow transformers capable of generating images from text descriptions. The FLUX.1-dev model is optimized for open research and innovation, while the FLUX.1-schnell model is focused on competitive performance. The flux-fp8 model aims to provide the same capabilities as these larger models, but with reduced memory and computational requirements through 8-bit floating point quantization.

Model inputs and outputs

The flux-fp8 model takes text descriptions as input and generates high-quality, photorealistic images as output. The model was trained using advanced techniques like latent adversarial diffusion distillation, which allows for fast image generation in just 1-4 steps.

Inputs

Text descriptions to guide the image generation process

Outputs

Photorealistic images generated from the input text descriptions

Capabilities

The flux-fp8 model is capable of generating a wide variety of images, from landscapes and cityscapes to portraits and abstract art. It can capture fine details and complex compositions, and has shown strong performance in prompt following compared to other open-source alternatives.

What can I use it for?

The flux-fp8 model can be used for a variety of creative and commercial applications, such as concept art, product visualization, and illustration. Developers and artists can incorporate the model into their workflows using the reference implementation and sampling code provided in the Black Forest Labs GitHub repository. The model is also available through API endpoints from bfl.ml, replicate.com, and fal.ai, making it accessible to a wide range of users.

Things to try

Experiment with different prompting styles and techniques to see how the flux-fp8 model responds. Try using more specific or detailed descriptions, or combining the model with other tools like ComfyUI for a node-based workflow. The quantized nature of the flux-fp8 model may also lead to interesting visual effects or artifacts that you can explore and incorporate into your creative projects.

This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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