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German artificial intelligence startup Black Forest Labs recently released a FLUX Pro fine-tuning API, through which users can customize the FLUX Pro AI image model using just five sample images to match the vision of a specific brand style.
According to Black Forest Labs, after fine-tuning, the model remains flexible and can incorporate user-provided content into new image creations. The system is capable of generating high-resolution images of up to four million pixels.
With the FLUX Pro fine-tuning API, creators can customize FLUX.1[pro] with their own images and concepts, giving them greater control over the final result. User-supplied images can be used to train FLUX Pro models, making each tweak a user-customized FLUX Pro model.
The fine-tuning API designed by Black Forest Labs is applicable to its entire product range. Customized models can be integrated with flagship products FLUX.1Pro and FLUX1.1Pro Ultra, and also support functions such as FLUX.1Fill (for image repair) and FLUX.1Depth (for image repair). Structural control) and other professional tools.
German media company Burda Verlag is using the FLUX fine-tuning API to create customized versions of image mockups for several of its brands. For example, the company's creative team is now able to generate images for children's brand Lissy PONY in minutes that match the brand's unique visual elements.
Looking at the technical details, the API supports common image formats including JPG, PNG and WebP files. Users can upload between 1 and 20 training images, with a maximum resolution of one million pixels per image. Black Forest Labs says that for best results you need at least five high-quality images that clearly define your subject.
Developers can adjust multiple training parameters, including training mode (role, product, style, or universal), number of training iterations (minimum 100, default 300), and learning rate. On the output side, developers can choose to train quickly for faster inference, or choose longer processing times to produce higher quality results.
In a user study, 68.9% of respondents preferred FLUX Pro fine-tuning results over other existing fine-tuning services.
Black Forest Labs has issued specific recommendations for different usage scenarios. For example, when training character models, it is recommended to use images that only show one character at a time; while in style transfer work, testing higher fine-tuning intensity often leads to better results.
Currently, the FLUX Pro fine-tuning API is still in beta and requires an API key to access. Black Forest Labs has yet to reveal pricing details or announce when the service will be generally available.
Official blog: https://blackforestlabs.ai/announcing-the-flux-pro-finetuning-api/
API entrance: https://docs.bfl.ml/
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