task_categories:text-generation size_categories:1M<n<10M source_datasets:tiiuae/falcon-refinedweb language:en license:mit arxiv:2306.01116 doi:10.57967/hf/1024 region:us
---
license: mit
viewer: true
task_categories:
- text-generation
language:
- en
pretty_name: Tiny WebText
size_categories:
- 1M<n<10M
source_datasets:
- tiiuae/falcon-refinedweb
---


# Tiny WebText

The Tiny WebText dataset is designed to help models learn about perception on web text while neutralizing the bias of the source text using critical thinking methods. By providing a rich and diverse set of texts, I aim to improve the ability of models to understand and analyze information in a more objective and unbiased manner.

This dataset can be used to train and evaluate natural language processing and machine learning models, with the goal of improving their perception and critical thinking skills. It is a valuable resource for researchers and developers, especially those working in the fields of machine learning and data engineering.

The dataset is augmented using subset of [Falcon-RefinedWeb](https://arxiv.org/abs/2306.01116), which provides additional augmented text using [Falcon-7B-Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct) model to improve the quality and diversity of the texts.

I welcome any feedback or contributions. Thank you for your interest in my work!