text-image
Z-Image_Qwen_3_4b_text_encoder_GGUFuform3-image-text-multilingual-baseQwen3-Uncensored-TextEncoders-Klein-Z-Image-Anima-GGUFQwen3-Uncensored-TextEncoders-FLUX-Klein-Z-Image-Turbo-GGUFQwen-Image-2.1-Text-Encoder-Heretic-GGUFText-to-Imageapply_texture_qwen_image_edit_2509SpydazWeb_AI_ImageText_Text_Project-i1-GGUF
text-to-image-promptsIf you have questions about this dataset , feel free to ask them on the fusion-discord : https://discord.gg/8TVHPf6Edn
This collection contains sets from the fusion-t2i-ai-generator on perchance.
This datset is used in this notebook: https://huggingface.co/datasets/codeShare/text-to-image-prompts/tree/main/Google%20Colab%20Notebooks
To see the full sets, please use the url "https://perchance.org/" + url
, where the urls are listed below:
_generator
gen_e621
fusion-t2i-e621-tags-1… See the full description on the dataset page: https://huggingface.co/datasets/codeShare/text-to-image-prompts.dummy_image_text_data
Dataset Card for "dummy_image_text_data"
More Information needed
Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-ForecastingThe sp500stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 4,213 S&P 500 stocks.
The hs300stock_data_description.csv file provides detailed information on the existence of four modalities (text, image, time series, and table) for 858 HS 300 stocks.
If you find our research helpful, please cite our paper:
@article{xu2025finmultitime,
title={FinMultiTime: A Four-Modal Bilingual Dataset for… See the full description on the dataset page: https://huggingface.co/datasets/Wenyan0110/Multimodal-Dataset-Image_Text_Table_TimeSeries-for-Financial-Time-Series-Forecasting.mscoco_2014_5k_test_image_text_retrieval
MSCOCO (5K test set)
Original paper: Microsoft COCO: Common Objects in Context
Homepage: https://cocodataset.org/#home
5K test set split from: http://cs.stanford.edu/people/karpathy/deepimagesent/caption_datasets.zip
Bibtex:
@inproceedings{lin2014microsoft,
title={Microsoft coco: Common objects in context},
author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence}… See the full description on the dataset page: https://huggingface.co/datasets/nlphuji/mscoco_2014_5k_test_image_text_retrieval.flickr_1k_test_image_text_retrieval
Flickr30k (1K test set)
Original paper: From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions
Homepage: https://shannon.cs.illinois.edu/DenotationGraph/
1K test set split from: http://cs.stanford.edu/people/karpathy/deepimagesent/caption_datasets.zip
Bibtex:
@article{young2014image,
title={From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions}… See the full description on the dataset page: https://huggingface.co/datasets/nlphuji/flickr_1k_test_image_text_retrieval.text-2-image-Rich-Human-Feedback
Building upon Google's research Rich Human Feedback for Text-to-Image Generation we have collected over 1.5 million responses from 152'684 individual humans using Rapidata via the Python API. Collection took roughly 5 days.
If you get value from this dataset and would like to see more in the future, please consider liking it.
Overview
We asked humans to evaluate AI-generated images in style, coherence and prompt alignment. For images that contained flaws, participants were… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-image-Rich-Human-Feedback.