Scaling Language-Centric Omnimodal Representation Learning
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Eric Lau
andywu-kby
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RasterScan/Automated-Floor-Plan-Digitalization
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We’re excited to launch the new Prompt Gallery, a curated collection designed to help creators, developers, and AI artists get better results in text-to-image generation — faster and with less guesswork.
Demo: https://miragic.ai/prompt-search
Whether you're exploring ideas, studying prompt engineering, or building your own image workflows, this gallery gives you instant access to high-quality prompts paired with their real generated outputs.
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Do you remember https://thispersondoesnotexist.com/ ? It was one of the first cases where the future of generative media really hit us. Humans are incredibly good at recognizing and analyzing faces, so they are a very good litmus test for any generative image model.
But none of the current benchmarks measure the ability of models to generate humans independently. So we built our own. We measure the models ability to generate a diverse set of human faces and using over 20'000 human annotations we ranked all of the major models on their ability to generate faces. Find the full ranking here:
https://app.rapidata.ai/mri/benchmarks/68af24ae74482280b62f7596
We have release the full underlying data publicly here on huggingface: https://huggingface.co/datasets/Rapidata/Face_Generation_Benchmark
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