Datasets:

krisbailey
/

falcon-refinedweb-1B

license: apache-2.0
task_categories:
  - text-generation
language:
  - en
tags:
  - falcon
  - refinedweb
  - 1B
  - parquet
  - web-refined
  - text-generation
  - clean-web-corpus
  - llm-pretrain
  - domain-agnostic
  - sentence-quality-filtered
  - huggingface-refinedweb
size_categories:
  - 1B<n<10B

Falcon RefinedWeb 1B

Dataset Description

This is a 1.01 Billion token subset of the tiiuae/falcon-refinedweb dataset. It was created by streaming the dataset with a large shuffle buffer to ensure a random, representative sample of the web data.

Motivation

RefinedWeb is a high-quality filtered web dataset, but the full version is massive. This 1B token slice provides a perfect testbed for evaluating model architecture changes or for use in curriculum learning experiments.

Dataset Details

Total Tokens: 1,005,000,041 (~1.01B)
Source: tiiuae/falcon-refinedweb
Method: Streamed with shuffle buffer (size=5000).
Format: Parquet (Snappy compression)
Producer: Kris Bailey (kris@krisbailey.com)

Usage

from datasets import load_dataset

ds = load_dataset("krisbailey/falcon-refinedweb-1B", split="train")
print(ds[0])

Subsets & Slicing

Since this dataset was randomly shuffled during creation, you can safely slice it to get smaller, representative datasets (e.g., for scaling laws experiments) without needing to download the full dataset.

# 100M Token Subset (approx 10%)
ds_100m = load_dataset("krisbailey/falcon-refinedweb-1B", split="train[:10%]")

# 500M Token Subset (approx 50%)
ds_500m = load_dataset("krisbailey/falcon-refinedweb-1B", split="train[:50%]")

Citation

@article{penedo2023refinedweb,
  title={The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only},
  author={Penedo, Guilherme and Malartic, Quentin and Hesslow, Daniel and Cojocaru, Ruxandra and Cappelli, Alessandro and Alobeidli, Hamza and Pannier, Baptiste and Almazrouei, Ebtesam and Launay, Julien},
  journal={arXiv preprint arXiv:2306.01116},
  year={2023}
}