README.md

metadata

license: odc-by
task_categories:
  - text-generation
language:
  - en
tags:
  - rp
  - 100M
  - parquet
  - redpajama
  - reference-reproduction
  - benchmark-subset
  - open-pretraining-data
  - reproducible-dataset
  - data-slicing
size_categories:
  - 100M<n<1B

RedPajama-Data-V2-100M

Dataset Description

This is a 100.0 Million token subset of krisbailey/RedPajama-Data-V2-1B, which is a subset of togethercomputer/RedPajama-Data-V2.

Motivation

100M tokens is a standard size for:

• CI/CD Pipelines: Fast enough to download and train for unit tests.
• Debugging: Verifying training loops without waiting for hours.
• Scaling Laws: The first step in a logarithmic scaling series (100M -> 1B -> 10B).

Dataset Details

• Total Tokens: 99,999,721
• Source: krisbailey/RedPajama-Data-V2-1B
• Structure: First ~10% of the randomized 1B dataset.
• Format: Parquet (Snappy compression) - Single File
• Producer: Kris Bailey (kris@krisbailey.com)

Usage

from datasets import load_dataset

ds = load_dataset("krisbailey/RedPajama-Data-V2-100M", split="train")
print(ds[0])

Citation

@article{together2023redpajama,
  title={RedPajama: An Open Source Recipe to Reproduce LLaMA training dataset},
  author={Together Computer},
  journal={https://github.com/togethercomputer/RedPajama-Data},
  year={2023}
}