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pick-style-pixel-art
- huggingface.co
Updated Jun 12, 2024
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EmailClick to copy linkLink copiedCiteMaPO (2024). pick-style-pixel-art [Dataset]. https://huggingface.co/datasets/mapo-t2i/pick-style-pixel-artCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedJun 12, 2024Dataset authored and provided byMaPOLicensehttps://choosealicense.com/licenses/openrail++/https://choosealicense.com/licenses/openrail++/
DescriptionMargin-aware Preference Optimization for Aligning Diffusion Models without Reference
We propose MaPO, a reference-free, sample-efficient, memory-friendly alignment technique for text-to-image diffusion models. For more details on the technique, please refer to our paper here.
Developed byJiwoo Hong* (KAIST AI) Sayak Paul* (Hugging Face) Noah Lee (KAIST AI) Kashif Rasul (Hugging Face) James Thorne (KAIST AI) Jongheon Jeong (Korea University)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/mapo-t2i/pick-style-pixel-art. - h
pick-style-cartoon
- huggingface.co
Updated Jun 12, 2024ShareFacebookTwitterEmailClick to copy linkLink copiedCiteMaPO (2024). pick-style-cartoon [Dataset]. https://huggingface.co/datasets/mapo-t2i/pick-style-cartoonCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedJun 12, 2024Dataset authored and provided byMaPOLicensehttps://choosealicense.com/licenses/openrail++/https://choosealicense.com/licenses/openrail++/
DescriptionMargin-aware Preference Optimization for Aligning Diffusion Models without Reference
We propose MaPO, a reference-free, sample-efficient, memory-friendly alignment technique for text-to-image diffusion models. For more details on the technique, please refer to our paper here.
Developed byJiwoo Hong* (KAIST AI) Sayak Paul* (Hugging Face) Noah Lee (KAIST AI) Kashif Rasul (Hugging Face) James Thorne (KAIST AI) Jongheon Jeong (Korea University)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/mapo-t2i/pick-style-cartoon. 
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FacebookTwitterEmailhttps://choosealicense.com/licenses/openrail++/https://choosealicense.com/licenses/openrail++/
Margin-aware Preference Optimization for Aligning Diffusion Models without Reference
We propose MaPO, a reference-free, sample-efficient, memory-friendly alignment technique for text-to-image diffusion models. For more details on the technique, please refer to our paper here.
Developed by
Jiwoo Hong* (KAIST AI) Sayak Paul* (Hugging Face) Noah Lee (KAIST AI) Kashif Rasul (Hugging Face) James Thorne (KAIST AI) Jongheon Jeong (Korea University)
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/mapo-t2i/pick-style-pixel-art.