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---
license: mit
dataset_info:
features:
- name: url
dtype: string
- name: tag
dtype: string
- name: text
dtype: string
- name: file_path
dtype: string
- name: dump
dtype: string
- name: file_size_in_byte
dtype: int64
- name: line_count
dtype: int64
splits:
- name: train
num_bytes: 254927419643
num_examples: 100920235
download_size: 147948949488
dataset_size: 254927419643
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
This code-related data from [Fineweb](https://huggingface.co/spaces/HuggingFaceFW/blogpost-fineweb-v1) was specifically used in [OpenCoder](https://huggingface.co/papers/2411.04905) pre-training.
We employ fastText in three iterative rounds to recall a final dataset of 55B code and math-related data.
You can find math-related data at [OpenCoder-LLM/fineweb-math-corpus](https://huggingface.co/datasets/OpenCoder-LLM/fineweb-math-corpus).
## Citation
```
@inproceedings{Huang2024OpenCoderTO,
title={OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models},
author={Siming Huang and Tianhao Cheng and Jason Klein Liu and Jiaran Hao and Liuyihan Song and Yang Xu and J. Yang and J. H. Liu and Chenchen Zhang and Linzheng Chai and Ruifeng Yuan and Zhaoxiang Zhang and Jie Fu and Qian Liu and Ge Zhang and Zili Wang and Yuan Qi and Yinghui Xu and Wei Chu},
year={2024},
url={https://arxiv.org/pdf/2411.04905}
}
```
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