README.md

---
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configs:
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- config_name: documentation
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- config_name: ir_cpp
  data_files:
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    path: ir_cpp/train-*
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  data_files:
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- config_name: stackoverflow
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    path: stackoverflow/train-*
- config_name: wikipedia
  data_files:
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    path: wikipedia/train-*
---

# StarCoder2 Extras

This is the dataset of extra sources (besides Stack v2 code data) used to train the [StarCoder2](https://arxiv.org/abs/2402.19173) family of models. It contains the following subsets:

- Kaggle (`kaggle`): Kaggle notebooks from [Meta-Kaggle-Code](https://www.kaggle.com/datasets/kaggle/meta-kaggle-code) dataset, converted to scripts and prefixed with information on the Kaggle datasets used in the notebook. The file headers have a similar format to Jupyter Structured but the code content is only one single script.
- StackOverflow (`stackoverflow`): stackoverflow conversations from this [StackExchange dump](https://archive.org/details/stackexchange).
- Issues (`issues`): processed GitHub issues, same as the Stack v1 issues.
- OWM (`owm`): the [Open-Web-Math](https://huggingface.co/datasets/open-web-math/open-web-math) dataset.
- LHQ (`lhq`): Leandro's High quality dataset, it is a compilation of high quality code files from: APPS-train, CodeContests, GSM8K-train, GSM8K-SciRel, DeepMind-Mathematics, Rosetta-Code, MultiPL-T, ProofSteps, ProofSteps-lean.
- Wiki (`wikipedia`): the English subset of the Wikipedia dump in [RedPajama](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T).
- ArXiv (`arxiv`): the ArXiv subset of [RedPajama](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) dataset, further processed the dataset only to retain latex source files and remove preambles, comments, macros, and bibliographies from these files.
- IR_language (`ir_cpp`, `ir_low_resource`, `ir_python`, `ir_rust`): these are intermediate representations of Python, Rust, C++ and other low resource languages.
- Documentation (`documentation`): documentation of popular libraries.

For more details on the processing of each subset, check the [StarCoder2 paper](https://arxiv.org/abs/2402.19173) or The Stack v2 [GitHub repository](https://github.com/bigcode-project/the-stack-v2/).

## Usage 

```python
from datasets import load_dataset

# replace `kaggle` with one of the config names listed above
ds = load_dataset("bigcode/starcoder2data-extras", "kaggle", split="train")
```

## Citation

```
@article{lozhkov2024starcoder,
  title={Starcoder 2 and the stack v2: The next generation},
  author={Lozhkov, Anton and Li, Raymond and Allal, Loubna Ben and Cassano, Federico and Lamy-Poirier, Joel and Tazi, Nouamane and Tang, Ao and Pykhtar, Dmytro and Liu, Jiawei and Wei, Yuxiang and others},
  journal={arXiv preprint arXiv:2402.19173},
  year={2024}
}
```