---
license: odc-by
language:
- en
task_categories:
- text-generation
pretty_name: lilm-pretrain
size_categories:
- 100K<n<1M
---

# lilm-pretrain

A static mixed pretraining dataset curated for a sub-200M language model.

Repository: `glouriousgautam/lilm-pretrain`

## Source mix

- `finepdfs`: `codelion/finepdfs-1B` config `default`, target 500,000,000 tokens
- `dclm_baseline`: `codelion/dclm-baseline-1B` config `default`, target 300,000,000 tokens
- `fineweb`: `HuggingFaceFW/fineweb` config `default`, target 40,000,000 tokens
- `fineweb_edu`: `codelion/fineweb-edu-1B` config `default`, target 200,000,000 tokens
- `finemath_4plus`: `HuggingFaceTB/finemath` config `finemath-4plus`, target 10,000,000 tokens

## Curation method

Each source is streamed and sampled with reservoir sampling using seed `20260604`. The sampled source shards are merged and deterministically shuffled into Parquet shards.

The `token_count` column is based on the source `token_count` field when available and otherwise on `HuggingFaceTB/SmolLM2-135M` tokenization.

## Produced dataset

- Rows: 574,501
- Estimated tokens: 1,050,011,322
- Parquet shards: 23

## Per-source result

- `finepdfs`: 89,924 rows, 500,003,682 tokens
- `dclm_baseline`: 229,952 rows, 300,001,747 tokens
- `fineweb`: 57,446 rows, 40,004,125 tokens
- `fineweb_edu`: 190,934 rows, 200,001,086 tokens
- `finemath_4plus`: 6,245 rows, 10,000,682 tokens

## Columns

- `text`: training text
- `source`: short source alias
- `source_dataset`: Hugging Face source dataset id
- `source_config`: source config/subset
- `source_split`: source split
- `source_row_id`: source identifier or stable hash
- `token_count`: estimated token count
- `sample_seed`: sampling seed
- `source_seen_index`: row position seen during streaming