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Datasets:
maxgfr
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skycmd-text

Tasks:
Fill-Mask
Modalities:
Text
Formats:
parquet
Languages:
English
French
Size:
100K - 1M
Tags:
skycmd
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skycmd-text / README.md
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maxgfr
skycmd 84c6d854: skycmd pretraining text and tokenizers
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metadata 
license: other
license_name: per-source
license_link: https://github.com/maxgfr/skycmd/blob/main/DATA_LICENSES.md
language:
  - en
  - fr
pretty_name: skycmd pretraining text and tokenizers
task_categories:
  - fill-mask
tags:
  - skycmd
configs:
  - config_name: dolma3_finemath
    data_files: data/dolma3_finemath.parquet
  - config_name: dolma3_science_pdfs
    data_files: data/dolma3_science_pdfs.parquet
  - config_name: dolma3_wiki_en
    data_files: data/dolma3_wiki_en.parquet
  - config_name: fineweb2_fr
    data_files: data/fineweb2_fr.parquet
  - config_name: fineweb_edu
    data_files: data/fineweb_edu.parquet
  - config_name: simplestories
    data_files: data/simplestories.parquet
  - config_name: tinystories
    data_files: data/tinystories.parquet
  - config_name: tinystories_fr
    data_files: data/tinystories_fr.parquet
  - config_name: txt360_europarl_fr
    data_files: data/txt360_europarl_fr.parquet
  - config_name: txt360_pg19
    data_files: data/txt360_pg19.parquet
  - config_name: txt360_stackexchange
    data_files: data/txt360_stackexchange.parquet

skycmd pretraining text and tokenizers

The text of skycmd's masked-language-model pretraining (s1 to s6), English and French, and the tokenizers trained on it. data/text is read by every model; data/text-open (non-web parts of Dolma 3 and TxT360) is read first by the s6 models.

Part of skycmd, tiny decision models trained from scratch in Rust that run in the browser. Written by sky-data fetch-text and sky-data fetch-text --set open (scripts/prepare-data.sh) at commit 84c6d854. Licences of every set: DATA_LICENSES.md.

Each row is one document: src (the source) and text. All of it is deduplicated exactly and with MinHash/LSH (word 5-grams, Jaccard >= 0.8). The tokenizers trained on it are in tokenizers/ (sky-data train-tokenizer --vocab N --num).

Sources and licences

Each config is one source and keeps its source's licence (share-alike sources stay share-alike). Attribution goes to the upstream authors; the conversion is ours.

config upstream licence how it is used rows
dolma3_finemath allenai/dolma3_mix-150B-1025 data/finemath-3plus odc-by (FineMath, Dolma 3) and CommonCrawl's terms of use shard 00000000, exact duplicates dropped 4,354
dolma3_science_pdfs allenai/dolma3_mix-150B-1025 data/olmocr_science_pdfs-science_math_and_technology odc-by (Dolma 3); the PDFs keep their authors' rights, see the Dolma 3 card shard 00000000, olmOCR transcriptions 1,517
dolma3_wiki_en allenai/dolma3_mix-150B-1025 data/dolma1_7-wiki-en odc-by (Dolma 3); Wikipedia and Wikibooks text CC-BY-SA-4.0 / GFDL shard 00000000 2,489
fineweb2_fr HuggingFaceFW/fineweb-2 (fra_Latn, shard train/000_00000) odc-by (and CommonCrawl's terms of use) first row groups, 34 MB 11,010
fineweb_edu HuggingFaceFW/fineweb-edu (sample/10BT, shard 000_00000) odc-by (and CommonCrawl's terms of use) first row groups, 37.5 MB 9,002
simplestories SimpleStories/SimpleStories mit story column, first row groups of train, 30 MB 24,248
tinystories roneneldan/TinyStories cdla-sharing-1.0 text column, first row groups of train, 30 MB 33,400
tinystories_fr btecsec/tinystories-fr cdla-sharing-1.0 French text, whole train split 20,000
txt360_europarl_fr IFM/TxT360 data/europarl (French rows) odc-by (TxT360); European Parliament proceedings, reuse authorised with acknowledgement up to 8 pieces per session, 15 MB 873
txt360_pg19 IFM/TxT360 data/pg19 odc-by (TxT360); the books are public domain (Project Gutenberg) up to 8 pieces of 20,000 characters per book 1,140
txt360_stackexchange IFM/TxT360 data/stackexchange odc-by (TxT360); Stack Exchange posts CC-BY-SA one shard, 15 MB 4,638

Files

file rows
data/dolma3_finemath.parquet 4,354
data/dolma3_science_pdfs.parquet 1,517
data/dolma3_wiki_en.parquet 2,489
data/fineweb2_fr.parquet 11,010
data/fineweb_edu.parquet 9,002
data/simplestories.parquet 24,248
data/tinystories.parquet 33,400
data/tinystories_fr.parquet 20,000
data/txt360_europarl_fr.parquet 873
data/txt360_pg19.parquet 1,140
data/txt360_stackexchange.parquet 4,638
tokenizers/tok-s2-1024.json —
tokenizers/tok-s6-2048.json —
tokenizers/tok-s6-4096.json — 
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-text", "dolma3_finemath")

skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.

TinyStories, TinyStories-fr and SimpleStories are synthetic stories written by language models upstream (see their cards); skycmd generated none of this text.