license: other
language:
- en
tags:
- synthetic
pretrain-60GB
A 60GB, knowledge-dense pretraining corpus built as a clean, superior alternative to TinyStories.
TinyStories teaches grammar. This teaches knowledge, reasoning, and code.
File: pretrain.csv - 60GB, ~15M rows, single column text
Why vs TinyStories?
TinyStories is fiction for kids. This is textbook / encyclopedia / reasoning / code. Every row is 3500-5200 chars packed with 2-3 fused concepts, not a story.
- Physics, Chem, Bio, Math, CS, History, Geo, Econ
- Step-by-step math with verification
- Algorithms with invariants + edge cases
- Logic puzzles with backtracking traces
All synthetic, original, cleaned. One line per example for fast streaming. No scraped data, no copyrighted text.
Usage
Streaming is recommended for 60GB:
from datasets import load_dataset
from transformers import AutoTokenizer
ds = load_dataset("YOUR_USERNAME/pretrain-60GB", streaming=True, split="train")
for row in ds:
print(row['text'][:500])
break
tok = AutoTokenizer.from_pretrained("gpt2")
def tokenize(ex):
return tok(ex["text"], truncation=True, max_length=1024)
ds_tokenized = ds.map(tokenize)
With PyTorch:
import pandas as pd
for chunk in pd.read_csv("pretrain.csv", chunksize=100000):
# your training loop
pass
Stats
- Size: 64.4 GB on disk (60 GiB target)
- Rows: ~15-18M
- Avg length: ~4000 chars / 600-900 tokens
- Format: CSV, header
text, quoted, UTF-8 - License: Apache 2.0
Limitations
Synthetic data - may contain simplified explanations. Intended as a base pretrain, fine-tune on curated data after.
License
This dataset uses the Open Data Attribution Training Disclosure License (ODATL‑1.0). You may learn more looking at the LICENSE file.