README.md

metadata

language:
  - en
license: other
license_name: public-domain-gutenberg-texts-and-cc0-metadata
license_link: LICENSE
task_categories:
  - text-generation
pretty_name: Talkie YaRN 32k Gutenberg Pre-1931 265M
size_categories:
  - 1K<n<10K
tags:
  - talkie
  - project-gutenberg
  - pre-1931
  - long-context
  - yarn
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl
      - split: validation
        path: validation.jsonl

Talkie YaRN 32k Gutenberg Pre-1931 265M

This dataset is the continued-pretraining corpus used for the Talkie YaRN 32k context-extension experiments, including the recommended checkpoint xlr8harder/talkie-1930-13b-yarn-32k-tf.

It was generated from common-pile/project_gutenberg_filtered, joined with a Gutenberg publication-year metadata table from Kaggle, yuvalschwartz/gutenberg-book-metadata-with-publication-years, then filtered to English public-domain books with publication years from 1500 through 1930. Project Gutenberg boilerplate markers were stripped and each book was capped at 500,000 characters.

Splits

Split	Rows	Talkie tokens	Notes
train	3,146	265,080,702	Used for continued pretraining
validation	65	5,074,819	Held-out continuation after the train manifest

The train JSONL was reconstructed from the surviving manifest after the original local file was lost. The reconstruction preserved the original Gutenberg ID order and per-book metadata from train.summary.json.

Files

• train.jsonl: training split, one book per line.
• validation.jsonl: validation split, one book per line.
• train.summary.json: train manifest with per-book metadata and Talkie token counts.
• validation.summary.json: validation manifest with per-book metadata and Talkie token counts.
• scripts/prepare_gutenberg_with_years.py: generation and reconstruction script.
• metadata/gutenberg_publication_years.csv: publication-year metadata used by the script.
• logs/prepare_train.log: reconstruction log for the train split.

Each JSONL row has this shape:

{"text": "...", "meta": {"gutenberg_id": "...", "publication_year": 1900, "...": "..."}}

Generation Command

The train split was reconstructed with:

python scripts/prepare_gutenberg_with_years.py \
  --dataset common-pile/project_gutenberg_filtered \
  --split train \
  --metadata-csv metadata/gutenberg_publication_years.csv \
  --out train.jsonl \
  --summary-out train.summary.json \
  --include-summary train.summary.json \
  --reuse-include-summary-token-counts \
  --min-year 1500 \
  --max-year 1930 \
  --languages en \
  --rights-contains "public domain" \
  --min-chars 100000 \
  --max-chars-per-book 500000 \
  --target-talkie-tokens 265000000 \
  --max-books 0

For a fresh build rather than manifest reconstruction, omit --include-summary and --reuse-include-summary-token-counts, and write to a new output path.

The validation split used the same filters while excluding the train manifest:

python scripts/prepare_gutenberg_with_years.py \
  --dataset common-pile/project_gutenberg_filtered \
  --split train \
  --metadata-csv metadata/gutenberg_publication_years.csv \
  --out validation.jsonl \
  --summary-out validation.summary.json \
  --exclude-summary train.summary.json \
  --min-year 1500 \
  --max-year 1930 \
  --languages en \
  --rights-contains "public domain" \
  --min-chars 100000 \
  --max-chars-per-book 500000 \
  --target-talkie-tokens 5000000 \
  --max-books 0

Integrity

• train.jsonl SHA-256: 50a0908c33e741ce96e9b8c75f266369aac7f1ccd76757970904031b487c283c
• validation.jsonl SHA-256: efa8f3218ec219aeb5ffd5cbe70b92c3bb42e4b599dbb74f3dde7dc4b256d21a

License Notes

This repository uses license: other with a custom license description because it combines multiple upstream sources. The text rows inherit the public-domain status reported by common-pile/project_gutenberg_filtered for the selected Project Gutenberg rows. The included publication-year metadata CSV comes from the Kaggle dataset yuvalschwartz/gutenberg-book-metadata-with-publication-years, which is listed as CC0: Public Domain. See LICENSE for the component-level license notes.