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goumsss
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๐ฆ I built a math app for my daughters โ and they already love it. NumZoo is a mental math trainer for kids. Answer questions, earn cute AI-generated animal rewards. My girls picked their favorite animals, chose a magical place, and haven't stopped playing since. โถ๏ธ Watch the demo: https://www.loom.com/share/c565cba49f2c4ad1bfb428e38ff4b629 ๐ฎ Try it: https://huggingface.co/spaces/build-small-hackathon/numzoo Stack: - ๐จ FLUX.2-klein-4B โ 4B params, Apache 2.0, 4 inference steps - ๐ผ๏ธ Custom kawaii style LoRA (trained on FLUX.2-klein-base-4B) - โก ZeroGPU ยท Gradio ยท Diffusers The LoRA: locking in a kawaii storybook style Out of the box, FLUX.2-klein is unpredictable โ same prompt, wildly different styles. Not great when you want every reward to feel cozy and on-brand for a 6-year-old. So I fine-tuned a style LoRA: 54 hand-curated scenes (12 animals ร 10 places), captioned with a NUMZOO. trigger and no style words โ the model learns the look from the images alone. Rank 32, 1500 steps, trained on a Modal A100 in ~45 min. Published here: https://huggingface.co/goumsss/numzoo-flux2-klein-lora Two performance tricks that made it feel instant: - Pre-generation: image generation starts in the background the moment the quiz begins. By the time a reward is earned (3 correct answers), the image is already ready. Zero wait. - Cold-start fix: from_pretrained runs at module scope on CPU, outside the ZeroGPU budget. Inside @GPU we only do .to("cuda") โ shaves the cold-start from potential timeout to ~1s. Built for the ๐ค Build Small Hackathon. Small model, real joy. ๐พ
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