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lucataco controlnet tile run with an api on replicate lucataco controlnet tile lucataco controlnet tile controlnet v1 1 tile version public 4 3k runs license github paper playground api examples readme versions examples view more examples run time and cost this model costs approximately 0 082 to run on replicate or 12 runs per 1 but this varies depending on your inputs it is also open source and you can run it on your own computer with docker this model runs on nvidia l40s gpu hardware predictions typically complete within 84 seconds the predict time for this model varies significantly based on the inputs readme implementation of lllyasviel control_v11f1e_sd15_tile in an effort to find a basic image enhancer to upscale sdxl images at 1024 up to 2048 about this checkpoint is a conversion of the original checkpoint into diffusers format it can be used in combination with stable diffusion such as runwayml stable diffusion v1 5 controlnet is a neural network structure to control diffusion models by adding extra conditions this checkpoint corresponds to the controlnet conditioned on tiled image conceptually it is similar to a super resolution model but its usage is not limited to that it is also possible to generate details at the same size as the input conditione image model details developed by lvmin zhang maneesh agrawala model type diffusion based text to image generation model language s english license the creativeml openrail m license is an open rail m license adapted from the work that bigscience and the rail initiative are jointly carrying in the area of responsible ai licensing see also the article about the bloom open rail license on which our license is based resources for more information github repository paper misc zhang2023adding title adding conditional control to text to image diffusion models author lvmin zhang and maneesh agrawala year 2023 eprint 2302 05543 archiveprefix arxiv primaryclass cs cv model created over 1 year ago