swype/instruct

---
license: mit
---
# A large instruct dataset

This dataset is a combination of multiple sources, including the GPT4All dataset, the Alpaca dataset from Stanford, custom generation using AllenAI augmentation, and some dataset augmentation from open-source Meta datasets. The dataset is split into 70% for training, 20% for validation, and 10% for testing.

## Description

The Swype.com dataset contains prompt and completion pairs for various tasks. It's an augmented version of the following datasets:

- [GPT4All](https://github.com/nomic-ai/gpt4all): A dataset containing a wide range of tasks for training and evaluating general-purpose language models.
- [Alpaca dataset from Stanford](https://github.com/tatsu-lab/stanford_alpaca): A dataset containing prompts, completions, and annotations for controllable text generation.
- Custom generation using [AllenAI augmentation](https://allenai.org): Augmentation performed using the advanced NLP tools provided by AllenAI.
- Some dataset augmentation from open-source Meta datasets: Additional augmentation from various open-source Meta datasets.

The dataset is designed for training and evaluating language models on diverse tasks, with a focus on controllable and instruction-based text generation.

## Dataset Structure

The dataset contains the following columns:

- `prompt`: The input prompt string, representing a task or question.
- `completion`: The output completion string, representing the answer or generated text based on the prompt.

## Citation

If you use this dataset in your research or work, please cite it as follows:

@misc{srikanth2023swypedataset,
author = {Srikanth Srinivas},
title = {Swype.com Dataset},
year = {2023},
publisher = {Swype.com},
howpublished = {\url{https://swype.com}},
email = {[e-mail]}
}

原始信息汇总

数据集概述

数据集名称

A large instruct dataset

数据集来源

• GPT4All
• Alpaca dataset from Stanford
• Custom generation using AllenAI augmentation
• Some dataset augmentation from open-source Meta datasets

数据集用途

用于训练和评估语言模型，特别是在可控和指令基础的文本生成方面。

数据集结构

包含以下列：

• prompt: 输入提示字符串，代表任务或问题。
• completion: 输出完成字符串，代表答案或基于提示生成的文本。

数据集划分

• 训练集: 70%
• 验证集: 20%
• 测试集: 10%

许可证

MIT

引用信息

@misc{srikanth2023swypedataset, author = {Srikanth Srinivas}, title = {Swype.com Dataset}, year = {2023}, publisher = {Swype.com}, howpublished = {url{https://swype.com}}, email = {[e-mail]} }