flux-dev
Maintainer: black-forest-labs - Last updated 12/8/2024
Model overview
flux-dev is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. It is part of a suite of models developed by Black Forest Labs, including the more capable flux-pro and the faster flux-schnell. flux-dev is a guidance-distilled variant, optimized for better prompt following and visual quality compared to the base model. It is available for use through partnerships with Replicate and FAL.
Model inputs and outputs
flux-dev takes in a text prompt, an aspect ratio, guidance strength, and output format as inputs. It then generates a corresponding image based on the prompt. The output is a URI pointing to the generated image.
Inputs
- Prompt: The text prompt describing the image to generate
- Aspect Ratio: The desired aspect ratio of the output image
- Guidance: The strength of the guidance for the image generation (ignored for
flux-schnell) - Seed: A random seed for reproducible generation
- Output Format: The format of the output image (e.g. webp, png)
- Output Quality: The quality setting when saving the output image (not relevant for .png)
Outputs
- Image URI: A URI pointing to the generated image
Capabilities
flux-dev is capable of generating high-quality, photorealistic images from a wide range of text prompts. It incorporates state-of-the-art techniques in text-to-image generation, such as Stable Diffusion and Imagen, to produce diverse and detailed outputs.
What can I use it for?
flux-dev can be used for a variety of creative and commercial applications, such as:
- Generating concept art or illustrations for games, films, or publications
- Creating custom stock images or product visualizations
- Exploring creative ideas and generating inspiration through visual prompts
Things to try
With flux-dev, you can experiment with different prompts to see the range of images it can generate. Try mixing genres, styles, and subjects to see the model's versatility. You can also play with the aspect ratio and guidance settings to achieve different aesthetic effects.
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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