---
dataset_info:
  features:
  - name: text
    dtype: string
  - name: id
    dtype: string
  - name: metadata
    struct:
    - name: date
      dtype: timestamp[us]
    - name: dump
      dtype: string
    - name: file_path
      dtype: string
    - name: int_score
      dtype: int64
    - name: language
      dtype: string
    - name: language_score
      dtype: float64
    - name: score
      dtype: float64
    - name: token_count
      dtype: int64
    - name: url
      dtype: string
  splits:
  - name: train
    num_bytes: 3479493957.7581863
    num_examples: 1001536
  download_size: 1983898608
  dataset_size: 3479493957.7581863
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

## Qwark Corpus

1 billion of the highest quality tokens on the internet, based on [HuggingFaceTB/smollm-corpus](https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus)'s `fineweb-edu-dedup` subset.

Filtering process:

| Step                                                   | Description                                            | Rows Remaining |
|--------------------------------------------------------|--------------------------------------------------------|----------------|
| 1. Stream dataset until 1M samples have been selected  | Keep only items without strange characters             | 1,000,000      |
| 2. Remove items with length > 50,000                   | Filter items exceeding 50,000 characters in length     | 998,420        |
| 3. Combine with a selection of 4,000 TED transcripts   | Add educational TED talk transcripts to the dataset    | 1,002,425      |
| 4. Filter and remove items containing strange characters | Clean items with strange characters after merging       | 1,002,425      |