This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation.
GEMRec-18K is a prompt-model interaction dataset with 18K images generated by 200 publicly-available generative models paired with a diverse set of 90 textual prompts. We randomly sampled a subset of 197 models from the full set of models (all finetuned from Stable Diffusion) on Civitai according to the popularity distribution (i.e., download counts) and added 3 original Stable Diffusion checkpoints (v1.4, v1.5, v2.1) from HuggingFace. All the model checkpoints have been converted to the Diffusers format. The textual prompts were drawn from three sources: 60 prompts were sampled from Parti Prompts; 10 prompts were sampled from Civitai by popularity; we also handcrafted 10 prompts following the prompting guide from DreamStudio, and then extended them to 20 by creating a shortened and simplified version following the tips from Midjourney. The textual prompts were classified into 12 categories: abstract, animal, architecture, art, artifact, food, illustration, people, produce & plant, scenery, vehicle, and world knowledge.
This work was supported through the NYU High Performance Computing resources, services, and staff expertise.
If you find our work helpful, please consider cite it as follows:
@article{guo2023towards,
title={Towards Personalized Prompt-Model Retrieval for Generative Recommendation},
author={Guo, Yuanhe and Liu, Haoming and Wen, Hongyi},
journal={arXiv preprint arXiv:2308.02205},
year={2023}
}
This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation.
GEMRec-18K is a prompt-model interaction dataset with 18K images generated by 200 publicly-available generative models paired with a diverse set of 90 textual prompts. We randomly sampled a subset of 197 models from the full set of models (all finetuned from Stable Diffusion) on Civitai according to the popularity distribution (i.e., download counts) and added 3 original Stable Diffusion checkpoints (v1.4, v1.5, v2.1) from HuggingFace. All the model checkpoints have been converted to the Diffusers format. The textual prompts were drawn from three sources: 60 prompts were sampled from Parti Prompts; 10 prompts were sampled from Civitai by popularity; we also handcrafted 10 prompts following the prompting guide from DreamStudio, and then extended them to 20 by creating a shortened and simplified version following the tips from Midjourney. The textual prompts were classified into 12 categories: abstract, animal, architecture, art, artifact, food, illustration, people, produce & plant, scenery, vehicle, and world knowledge.
This work was supported through the NYU High Performance Computing resources, services, and staff expertise.
If you find our work helpful, please consider cite it as follows:
@article{guo2023towards,
title={Towards Personalized Prompt-Model Retrieval for Generative Recommendation},
author={Guo, Yuanhe and Liu, Haoming and Wen, Hongyi},
journal={arXiv preprint arXiv:2308.02205},
year={2023}
}