Exploring the intersection of ๐’‰๐’–๐’Ž๐’‚๐’ creativity ๐Ÿ‘ฅ and ๐‘จ๐‘ฐ ๐Ÿค– to achieve new heights in design aesthetics. We're unlocking technology to reach this goal.

Joined July 2024
Proud that our HF port of GenPoster100k (org. SAGE paper) was featured in a recent AI compliance study! Out of 11,682 datasets, ours was named an ๐’†๐’™๐’„๐’†๐’‘๐’•๐’Š๐’๐’๐’‚๐’๐’๐’š ๐’“๐’‚๐’“๐’†, gold-standard example of a highly detailed Dataset Card. ๐Ÿงต Links to the papers & dataset below
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๐Ÿ”— Links & Resources: ๐Ÿ“„ The compliance study (Highlighting our Dataset Card): arxiv.org/abs/2607.03310 ๐Ÿ—„๏ธ Our Hugging Face release (GenPoster100K): huggingface.co/datasets/creaโ€ฆ ๐Ÿ“ The original dataset paper (SAGE): arxiv.org/abs/2510.15749
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What if we applied the concept ๐พ๐‘Ž๐‘Ÿ๐‘๐‘Ž๐‘กโ„Ž๐‘ฆ'๐‘  ๐ฟ๐ฟ๐‘€ ๐‘ค๐‘–๐‘˜๐‘– to creative graphic design?
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Weโ€™re building ๐˜พ๐™ง๐™š๐™–๐™ฉ๐™ž๐™ซ๐™š ๐™‚๐™ง๐™–๐™ฅ๐™๐™ž๐™˜ ๐˜ฟ๐™š๐™จ๐™ž๐™œ๐™ฃ ๐˜ฟ๐™–๐™ฉ๐™–๐™จ๐™š๐™ฉ๐™จ, a growing collection of 20+ Hugging Face๐Ÿค—-ready datasets for graphic design generation and evaluation. From posters and banners to UIs, typography, layouts, ads, evaluation, and more. Link below ๐Ÿ‘‡
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Released a FastAPI server for image layer decomposition using Qwen-Image-Layered! โœจ๏ธ Automatically decompose images into semantic layers โšก๏ธ FastAPI + GPU acceleration ๐Ÿ› ๏ธ Simple REST API GitHub: github.com/creative-graphic-โ€ฆ
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๐Ÿ”ฅ Want LongCLIP in a familiar API? Now you can use LongCLIP with a Transformers-compatible API โ€” load models like any other ๐Ÿค— Transformers model and run long-text vision-language inference with the `.from_pretrained` function. โ† After & Before โ†’ ๐Ÿš€ Link in the next tweet ๐Ÿ‘‡
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๐ŸŽ‰ Happy New Year! Start 2026 with smarter layout evaluation ๐ŸŽจโœจ Check out the Layout Evaluation Metrics for ๐Ÿค— Hugging Face Evaluate โ€“ tools to benchmark and score layout generation with ease. ๐Ÿš€ link in the next post! ๐Ÿ‘‡
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๐Ÿš€ Just dropped: gpt-graphic-design-evaluator โ€” a LangChain-powered system to automatically evaluate graphic design via LLMs! ๐Ÿ“ Based on the paper โ€œCan GPTs Evaluate Graphic Design Based on Design Principles?โ€ arxiv.org/abs/2410.08885 ๐Ÿ’ก Check it out: github.com/creative-graphic-โ€ฆ
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๐Ÿ’ญ Iโ€™ve seen some researchers who have been working on creative graphic design research recently move to Canva ๐Ÿง
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> F Lite is a 10B parameter diffusion model created by Freepik and Fal, trained exclusively on copyright-safe and SFW content. The model was trained on Freepik's internal dataset comprising approximately 80 million copyright-safe images huggingface.co/Freepik/F-Litโ€ฆ
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๐Ÿš€ Introducing lighting-diffusers: your template for diffusion model training with ๐Ÿค—Diffusers & โšกPyTorch Lightning! With full LightningCLI support, load all experiment settings from YAML filesโ€”making workflows reproducible, transparent, and manageable. github.com/creative-graphic-โ€ฆ
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Thrilled to share our published #SSII2024 technical map, showcasing the evolution of layout and poster generation research from 1990 to 2024! Excited to see how the field evolves with future directions in creative design๐Ÿ˜˜ ๐Ÿ—บ๏ธ bit.ly/ssii2024-techmap-creaโ€ฆ ๐Ÿ“Š bit.ly/ssii2024-techmap-creaโ€ฆ
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๐Ÿ“ฃ Our partner has released ๐™ช๐™ ๐™ž๐™ฎ๐™ค-๐™š-๐™›๐™–๐™˜๐™š-๐™—๐™ก๐™ž๐™ฅ๐Ÿฎ-๐™˜๐™–๐™ฅ๐™ฉ๐™ž๐™ค๐™ฃ๐™จ dataset, which is a Ukiyo-e dataset with captions added using BLIP2. We intend to use this dataset in LoRA tutorials and other such materials: ๐Ÿค— huggingface.co/datasets/py-iโ€ฆ ๐Ÿ™ github.com/py-img-gen/hugginโ€ฆ
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