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num_examples: 6315233
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download_size: 27160071916
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dataset_size: 56294728333.0
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- config_name: pull_requests
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features:
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- name: content
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dtype: string
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- name: guid
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dtype: string
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- name: ctx-size
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dtype: int64
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splits:
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- name: train
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num_bytes: 52871142902.97541
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num_examples: 2555843
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download_size: 16638673686
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dataset_size: 52871142902.97541
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- config_name: stackoverflow
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features:
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- name: date
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data_files:
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- split: train
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path: owm/train-*
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- config_name: pull_requests
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data_files:
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- split: train
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path: pull_requests/train-*
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- config_name: stackoverflow
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data_files:
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- split: train
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path: wikipedia/train-*
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---
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#
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- 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.
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- Pull Requests: processed GitHub Pull Requests.
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- StackOverflow: stackoverflow conversations from this [StackExchnage dump}(https://archive.org/details/stackexchange).
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- Issues: processed GitHub issues.
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- Owm: [Open-Web-math](https://huggingface.co/datasets/open-web-math/open-web-math) dataset.
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- 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.
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- Wiki: the english subset of the wikipedia dump in [RedPajama](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T).
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- Arxiv: 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.
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- IR_language: these are intermediate representations of Python, Rust, C++ and other low resource languages.
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- Documentation: documentation of popular libraries.
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num_examples: 6315233
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download_size: 27160071916
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dataset_size: 56294728333.0
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- config_name: stackoverflow
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features:
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- name: date
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data_files:
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- split: train
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path: owm/train-*
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- config_name: stackoverflow
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data_files:
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- split: train
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path: wikipedia/train-*
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---
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# StarCoder2 Extras
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This is the dataset of extra sources (besides Stack v2 code data) used to train the StarCoder2 family of models. It contains the following subsets:
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- Jupyter Scripts (`jupyter_scripts`): Jupyter notebooks from The Stack v2 converted to scripts.
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- Jupyter Structured (`jupyter_structured`): Jupyter notebooks from The Stack v2 converted to a structured format of code, markdown & output cells.
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- 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.
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- StackOverflow (`stackoverflow`)): stackoverflow conversations from this [StackExchnage dump](https://archive.org/details/stackexchange).
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- Issues (`issues`): processed GitHub issues, same as the Stack v1 issues.
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- OWM (`owm`): the [Open-Web-Math](https://huggingface.co/datasets/open-web-math/open-web-math) dataset.
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- 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.
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- Wiki (`wikipedia`): the English subset of the Wikipedia dump in [RedPajama](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T).
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- 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.
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- IR_language (`ir_cpp`, `ir_low_resource`, `ir_python`, `ir_rust`): these are intermediate representations of Python, Rust, C++ and other low resource languages.
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- Documentation (`documentation`): documentation of popular libraries.
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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/).
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## Usage
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```python
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from datasets import load_dataset
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# replace `jupyter_scripts` with one of the config names listed above
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ds = load_dataset("bigcode/starcoder2data-extras", "jupyter_scripts", split="train")
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```
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