---
license: odc-by
pretty_name: OLMoE-mix-0824 50B-token subset (dolma2 tokenizer)
language:
- en
task_categories:
- text-generation
tags:
- pretraining
- olmo
- olmo-core
---

# OLMoE-mix-0824, 50B-token subset (dolma2-tokenized)

A 50.0B-token, source-proportional subset of **OLMoE-mix-0824**, the pretraining mix of the
standard OLMo2 model ladder in [OLMo-core](https://github.com/allenai/OLMo-core) (≤ v2.4.0,
`src/scripts/train/OLMo2/OLMo2-ladder.py`). It also includes the full
**v3-small perplexity validation sets** used by that ladder. Everything is pre-tokenized with
the `allenai/dolma2-tokenizer` and laid out exactly like `http://olmo-data.org`, so OLMo-core can
read it with `mix_base_dir` / `--data-root` pointed at a local download of this repo.

50B tokens covers a 10×Chinchilla run of the 190M ladder model (38.07B tokens) in under one epoch.

## Contents

| split | files | tokens | size |
|---|---|---|---|
| train (`preprocessed/`) | 21 | 50.000B | 200.0 GB |
| validation (`eval-data/perplexity/v3_small_dolma2-tokenizer/`) | 11 | 6.69M | 26.7 MB |

Train composition (identical to the full mix's token shares):

| source | tokens | share |
|---|---|---|
| dclm | 47.55B | 95.10% |
| starcoder | 1.07B | 2.14% |
| pes2o | 0.76B | 1.51% |
| proofpile-2-arxiv | 0.27B | 0.54% |
| proofpile-2-open-web-math | 0.16B | 0.31% |
| proofpile-2-stack | 0.15B | 0.31% |
| wikipedia | 0.05B | 0.09% |

Validation sets: c4_en, dolma_books, dolma_common-crawl, dolma_pes2o, dolma_reddit, dolma_stack,
dolma_wiki, ice, m2d2_s2orc, pile, wikitext_103.

## How the subset was made

Each source gets a token budget proportional to its share of the full mix (3.875T tokens, 1,117
files). Within a source, files are taken whole in a seeded random order (seed 34521), and the
budget is topped off with a **prefix** of one more file. Those files are named
`*.prefix<NUM_BYTES>.npy`. `subset_plan.tsv` lists every file with its original path and the
number of bytes taken; `train_files.txt` lists the train files as `label,path` lines.

## File format

Each `.npy` file is a **raw `uint32` token array with no NumPy header** (the OLMo convention),
i.e. read it with `numpy.memmap(path, dtype=numpy.uint32, mode="r")`. Documents are separated by
the EOS token (id 100257).

## Usage with OLMo-core

```python
from olmo_core.data import NumpyFSLDatasetConfig, TokenizerConfig

root = "/path/to/olmo-data-50B"
paths = [f"{root}/{line.split(',', 1)[1].strip()}" for line in open(f"{root}/train_files.txt")]
dataset = NumpyFSLDatasetConfig(
    paths=paths, sequence_length=2048, tokenizer=TokenizerConfig.dolma2(), work_dir="/tmp/olmo-work"
)
```

For validation, use `DataMix.v3_small_ppl_validation` with `mix_base_dir=root`.

## License and attribution

The data is a redistribution of a subset of AI2's OLMoE-mix-0824 (downloaded from
`http://olmo-data.org`), released under the
[ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) license. Each component keeps its
original license and terms of use (e.g. DCLM, The Stack / StarCoder data, peS2o, Proof-Pile-2,
Wikipedia); please consult them before use. Credit: Allen Institute for AI (OLMo / OLMoE).