Datasets:
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license: apache-2.0
task_categories:
- text-generation
- fill-mask
language:
- en
size_categories:
- 1B<n<10B
---
# LM1B - One Billion Word Benchmark
## Dataset Description
The One Billion Word Benchmark is a large language modeling dataset.
It contains approximately one billion words of training data derived from news articles.
## How was this dataset built?
We download the full LM1B dataset from TensorFlow Datasets (TFDS) and convert it to HuggingFace format automatically. The full script is in `lm1b.py`. The required environment is:
- tensorflow==2.20.0
- tensorflow-datasets==4.9.9
- huggingface_hub==1.3.3
- datasets==4.4.1
```bash
pip install tensorflow==2.20.0 tensorflow-datasets==4.9.9 huggingface_hub==1.3.3 datasets==4.4.1
python lm1b_builder.py --action all
```
## Dataset Structure
### Data Fields
- `text`: A string containing the text content
### Data Splits
| Split | Examples |
|-------|----------|
| train | 30,301,028 |
| test | 306,688 |
## Citation
```bibtex
@inproceedings{chelba2013one,
title={One billion word benchmark for measuring progress in statistical language modeling},
author={Chelba, Ciprian and Mikolov, Tomas and Schuster, Mike and Ge, Qi and Brants, Thorsten and Koehn, Phillipp and Robinson, Tony},
booktitle={Interspeech},
year={2014}
}
```
## License
Apache 2.0
|