Ereeeeef3/Qu-QA

---
license: apache-2.0
tags:
- code
- gsm8k
- QA
size_categories:
- 1M<n<10M
language:
- en
datasets:
- qu_qa
configurations:
- default
task_categories:
- question-answering
---

# Qu QA Dataset

Qu QA is a large-scale question-answering (QA) dataset designed for training and evaluating machine learning models. It consists of question-answer pairs in English, making it suitable for general-purpose QA tasks, as well as specialized domains like code-related question answering and GSM8k-style problems.

## Dataset Details

- **Features:**
- `input`: A string representing the question (dtype: string).
- `output`: A string representing the answer (dtype: string).

- **Splits:**
- `train`: 4,343,971 examples (4.8 GB)

- **Total dataset size:** ~4.8 GB
- **Download size:** ~2.5 GB

## Dataset Viewer

You can view and explore the Qu QA dataset interactively on the Hugging Face platform using the following link:

[Qu QA Dataset Viewer](https://huggingface.co/datasets/Ereeeeef3/Qu-QA?row=0)

## Usage

You can easily load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

# Load the Qu QA dataset
dataset = load_dataset("Ereeeeef3/Qu-QA")

# Access the train split
train_dataset = dataset["train"]
print(train_dataset[0])

Qu QA is a large-scale question-answering (QA) dataset designed for training and evaluating machine learning models. It consists of question-answer pairs in English, making it suitable for general-purpose QA tasks, as well as specialized domains like code-related question answering and GSM8k-style problems. The dataset features include: `input` field representing the question (dtype: string), `output` field representing the answer (dtype: string). The dataset is split into `train` with 4,343,971 examples, total dataset size of ~4.8 GB, and download size of ~2.5 GB.

搜集汇总

背景与挑战

背景概述

Qu-QA是一个大规模英语问答数据集，包含约434万条问答对，适用于训练和评估机器学习模型，特别涵盖代码相关和GSM8k风格的数学问题。数据集采用parquet格式，大小为约4.8 GB，标签包括code、gsm8k和QA，许可证为Apache 2.0。