---
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.