# Qwen3-Inspired Pre-training Dataset

## Overview

This dataset is a curated mixture of high-quality text data designed for large language model pre-training, inspired by the Qwen3 methodology.

## Dataset Statistics

**Total Size:** 10.19 billion tokens

### Data Sources

- **dclm_baseline**: 6.21B tokens (60.92%) - 4,973,695 documents
- **mini_pile**: 1.43B tokens (14.04%) - 999,249 documents
- **common_corpus**: 1.01B tokens (9.87%) - 246,160 documents
- **the_stack**: 0.96B tokens (9.4%) - 248,650 documents
- **math_pile**: 0.59B tokens (5.77%) - 66,729 documents


## Data Processing Pipeline

1. **Data Collection**: Sourced from multiple high-quality datasets
2. **Standardization**: All data transformed to consistent format with `text`, `info`, and `source_data` fields  
3. **Exact Deduplication**: Removed identical documents
4. **Near Deduplication**: Used MinHashLSH with Jaccard similarity threshold of 0.85
5. **Quality Filtering**: Applied content-based filtering during processing

## Data Format

Each example contains:
- `text`: The main text content
- `info`: Metadata from the original dataset (as string)
- `source_data`: Source dataset identifier

## Tokenization

Token counts were computed using the Llama3 tokenizer (`meta-llama/Meta-Llama-3-8B`).

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("bluelightai-dev/qwen_clt_pretrain_data")
```

## Dataset Sources

The dataset combines data from the following sources:
- **DCLM Baseline**: High-quality web text from DataComp-LM
- **Common Corpus**: Multilingual web text corpus
- **The Stack**: Deduplicated source code
- **Mini Pile**: Academic and reference texts
- **Math Pile**: Mathematical content and reasoning datasets

## License

Please refer to the individual source dataset licenses. This mixture is provided for research purposes.

## Citation

If you use this dataset, please cite the original source datasets and this work.