datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
docvqa-single-page-questions
Dataset Card for DocVQA Dataset
Dataset Summary
DocVQA dataset is a document dataset introduced in Mathew et al. (2021) consisting of 50,000 questions defined on 12,000+ document images.
Please visit the challenge page (https://rrc.cvc.uab.es/?ch=17) and paper (https://arxiv.org/abs/2007.00398) for further information.
Usage
This dataset can be used with current releases of Hugging Face datasets library.
Here is an example using a custom collator to bundle… See the full description on the dataset page: https://huggingface.co/datasets/pixparse/docvqa-single-page-questions.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/eQOURSE/jee-main-questions.jee-advanced-questions
JEE Advanced — Question Bank
A structured dataset of JEE Advanced examination questions with full
worked solutions and diagrams. JEE Advanced questions are more analytical
than JEE Main — many are subjective, integer, or numerical-answer type with
detailed multi-step solutions.
Subsets (PCM):
Physics — 50 questions
Chemistry — 21 questions
Mathematics — 48 questions
Structure
Organised into subsets by subject and splits (train / test):
mathematics/ physics/… See the full description on the dataset page: https://huggingface.co/datasets/eQOURSE/jee-advanced-questions.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/soughed/jee-main-questions.Turkish-medical-visual-question-answering-LLaVa-dataset
Türkçe Radyoloji Görüntüleme Veri Seti - data_RAD
data_RAD veri seti, radyoloji görüntüleri üzerinde görsel soru-cevaplama (VQA) araştırmaları yapmak amacıyla Türkçeye çevrilmiş ve LLaVa mimarisiyle uyumlu hale getirilmiştir. Bu veri seti, tıbbi görüntü analizi ve yapay zeka destekli radyoloji uygulamalarını geliştirmek için kullanılabilir.
Veri Seti İçeriği
Toplam Görüntü Sayısı: 316
Veri Yapısı: DatasetDict({ train: Dataset({ features: ['image'], num_rows: 316 }) })
Özellikler:… See the full description on the dataset page: https://huggingface.co/datasets/nezahatkorkmaz/Turkish-medical-visual-question-answering-LLaVa-dataset.docvqa-single-page-questions-answer-ocr
DocVQA with Answer Localization
This dataset provides answer-localization annotations produced by our pipeline on top of the DocVQA dataset.
Usage
from datasets import load_dataset
# Load the dataset with answer OCR annotations
ds = load_dataset("indrehus/docvqa-single-page-questions-answer-ocr", split="validation")
# Get a single sample
sample = ds[0]
# Available fields in each sample:
print("Image:", sample["image"]) # PIL.Image
print("Question:"… See the full description on the dataset page: https://huggingface.co/datasets/indrehus/docvqa-single-page-questions-answer-ocr.jee-advanced-questions
JEE Advanced — Question Bank
A structured dataset of JEE Advanced examination questions with full
worked solutions and diagrams. JEE Advanced questions are more analytical
than JEE Main — many are subjective, integer, or numerical-answer type with
detailed multi-step solutions.
Subsets (PCM):
Physics — 50 questions
Chemistry — 21 questions
Mathematics — 48 questions
Structure
Organised into subsets by subject and splits (train / test):
mathematics/ physics/… See the full description on the dataset page: https://huggingface.co/datasets/Grass-G/jee-advanced-questions.jee-main-questions
JEE Main — Question Bank
A structured dataset of JEE Main examination questions with full metadata,
worked solutions, and diagrams. Built for education, ML training, and
question-generation use cases.
Subsets:
Chemistry — 738 questions from 28 papers
Physics — 768 questions from 28 papers
Mathematics — 801 questions from 28 papers
Over 2,300 questions across the three core JEE subjects.
Structure
Organised into subsets by subject and splits (train / test):… See the full description on the dataset page: https://huggingface.co/datasets/Grass-G/jee-main-questions.Iranian_olympiad_of_informatics_multimodal_questionsdocvqa-single-page-questions-answer-ocr-colSmol500M-q-priors
DocVQA Evidence Heatmaps (colsmol-500M)
This dataset contains question–evidence aligned heatmaps produced by our pipeline using colsmol-500M. It is intended as an auxiliary artifact to accompany our main dataset:
Main dataset (DocVQA with Answer Localization): https://huggingface.co/datasets/indrehus/docvqa-single-page-questions-answer-ocr
Usage
from datasets import load_dataset
# Load the dataset with ColSmol-500M question priors
ds = load_dataset(… See the full description on the dataset page: https://huggingface.co/datasets/indrehus/docvqa-single-page-questions-answer-ocr-colSmol500M-q-priors.ImageText-Question-answer-pairs-58K-Claude-3.5-Sonnnet
REILX/ImageText-Question-answer-pairs-58K-Claude-3.5-Sonnnet
从VisualGenome数据集V1.2中随机抽取21717张图片，利用Claude-3-opus-20240229和Claude-3-sonnet-20240620两个模型生成了总计58312个问答对，每张图片约3个问答，其中必有一个关于图像细节的问答。Claude-3-opus-20240229模型贡献了约3,028个问答对，而Claude-3-sonnet-20240620模型则生成了剩余的问答对。
Code
使用以下代码生成问答对：
# -*- coding: gbk -*-
import os
import random
import shutil
import re
import json
import requests
import base64
import time
from tqdm import tqdm
from json_repair import repair_json… See the full description on the dataset page: https://huggingface.co/datasets/REILX/ImageText-Question-answer-pairs-58K-Claude-3.5-Sonnnet.religious-questions-and-answers
Main fields
article_id, url, title, question, short_answer, content_html,
content_text, published_at_persian, view_count, and category fields.
is_valid_article marks archive links that resolved to a valid article page.