# GEMRec-18k -- Prompt Book
This is the official image dataset for the paper [Towards Personalized Prompt-Model Retrieval for Generative Recommendation](https://github.com/MAPS-research/GEMRec). 

## Dataset Intro
`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](https://civitai.com/) 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](https://huggingface.co/docs/diffusers/index) format. The textual prompts were drawn from three sources: 60 prompts were sampled from [Parti Prompts](https://github.com/google-research/parti); 10 prompts were sampled from [Civitai](https://civitai.com/) by popularity; we also handcrafted 10 prompts following the prompting guide from [DreamStudio](https://beta.dreamstudio.ai/prompt-guide), and then extended them to 20 by creating a shortened and simplified version following the tips from [Midjourney](https://docs.midjourney.com/docs/prompts). The textual prompts were classified into 12 categories: abstract, animal, architecture, art, artifact, food, illustration, people, produce & plant, scenery, vehicle, and world knowledge.

## Links
#### Dataset
- [GEMRec-Promptbook](https://huggingface.co/datasets/MAPS-research/GEMRec-PromptBook): The full version of our GemRec-18k dataset (images & metadata).
- [GEMRec-Metadata](https://huggingface.co/datasets/MAPS-research/GEMRec-Metadata): The pruned version of our GemRec-18k dataset (metadata only).
- [GEMRec-Roster](https://huggingface.co/datasets/MAPS-research/GEMRec-Roster): The metadata for the 200 model checkpoints fetched from [Civitai](https://civitai.com/).

#### Space
- [GEMRec-Gallery](https://huggingface.co/spaces/MAPS-research/GEMRec-Gallery): Our web application for browsing and comparing the generated images.

#### Github Code
- [GEMRec](https://github.com/MAPS-research/GEMRec)


## Acknowledgement
This work was supported through the NYU High Performance Computing resources, services, and staff expertise.

## Citation
If you find our work helpful, please consider cite it as follows:
```bibtex
@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}
}
```
task_categories:text-to-image size_categories:10K<n<100K language:en license:openrail art stable diffusion diffusers region:us
{"language": ["en"], "license": "openrail", "size_categories": ["10K<n<100K"], "task_categories": ["text-to-image"], "dataset_info": {"features": [{"name": "image", "dtype": "image"}, {"name": "image_id", "dtype": "string"}, {"name": "tag", "dtype": "string"}, {"name": "model_id", "dtype": "int64"}, {"name": "modelVersion_id", "dtype": "int64"}, {"name": "prompt_id", "dtype": "int64"}, {"name": "size", "dtype": "string"}, {"name": "seed", "dtype": "int64"}, {"name": "prompt", "dtype": "string"}, {"name": "negativePrompt", "dtype": "string"}, {"name": "cfgScale", "dtype": "int64"}, {"name": "sampler", "dtype": "string"}, {"name": "note", "dtype": "string"}, {"name": "nsfw_score", "dtype": "float64"}, {"name": "mcos_score", "dtype": "float64"}, {"name": "clip_score", "dtype": "float64"}, {"name": "norm_clip", "dtype": "float64"}, {"name": "norm_mcos", "dtype": "float64"}, {"name": "norm_nsfw", "dtype": "float64"}, {"name": "norm_pop", "dtype": "float64"}], "splits": [{"name": "train", "num_bytes": 10373652334, "num_examples": 18000}], "download_size": 9873105007, "dataset_size": 10373652334}, "tags": ["art", "stable diffusion", "diffusers"]}
TAGS
#task_categories-text-to-image #size_categories-10K<n<100K #language-English #license-openrail #art #stable diffusion #diffusers #region-us 

# GEMRec-18k -- Prompt Book
This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation. 

## Dataset Intro
'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.

## Links
#### Dataset
- GEMRec-Promptbook: The full version of our GemRec-18k dataset (images & metadata).
- GEMRec-Metadata: The pruned version of our GemRec-18k dataset (metadata only).
- GEMRec-Roster: The metadata for the 200 model checkpoints fetched from Civitai.

#### Space
- GEMRec-Gallery: Our web application for browsing and comparing the generated images.

#### Github Code
- GEMRec


## Acknowledgement
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:

# GEMRec-18k -- Prompt Book
This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation. ## Dataset Intro
'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. ## Links #### Dataset
- GEMRec-Promptbook: The full version of our GemRec-18k dataset (images & metadata).
- GEMRec-Metadata: The pruned version of our GemRec-18k dataset (metadata only).
- GEMRec-Roster: The metadata for the 200 model checkpoints fetched from Civitai. #### Space
- GEMRec-Gallery: Our web application for browsing and comparing the generated images. #### Github Code
- GEMRec ## Acknowledgement
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:
TAGS
#task_categories-text-to-image #size_categories-10K<n<100K #language-English #license-openrail #art #stable diffusion #diffusers #region-us 
 # GEMRec-18k -- Prompt Book
This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation. ## Dataset Intro
'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. ## Links #### Dataset
- GEMRec-Promptbook: The full version of our GemRec-18k dataset (images & metadata).
- GEMRec-Metadata: The pruned version of our GemRec-18k dataset (metadata only).
- GEMRec-Roster: The metadata for the 200 model checkpoints fetched from Civitai. #### Space
- GEMRec-Gallery: Our web application for browsing and comparing the generated images. #### Github Code
- GEMRec ## Acknowledgement
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:
passage: TAGS
#task_categories-text-to-image #size_categories-10K<n<100K #language-English #license-openrail #art #stable diffusion #diffusers #region-us 
# GEMRec-18k -- Prompt Book
This is the official image dataset for the paper Towards Personalized Prompt-Model Retrieval for Generative Recommendation.## Dataset Intro
'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.## Links#### Dataset
- GEMRec-Promptbook: The full version of our GemRec-18k dataset (images & metadata).
- GEMRec-Metadata: The pruned version of our GemRec-18k dataset (metadata only).
- GEMRec-Roster: The metadata for the 200 model checkpoints fetched from Civitai.#### Space
- GEMRec-Gallery: Our web application for browsing and comparing the generated images.#### Github Code
- GEMRec