--- dataset_info: - config_name: arxiv features: - name: content dtype: string splits: - name: train num_bytes: 89223183645.0 num_examples: 1558306 download_size: 40911186876 dataset_size: 89223183645.0 - config_name: documentation features: - name: project dtype: string - name: source dtype: string - name: language dtype: string - name: content dtype: string splits: - name: train num_bytes: 5421472234.0 num_examples: 59733 download_size: 1853451922 dataset_size: 5421472234.0 - config_name: ir_cpp features: - name: __index_level_0__ dtype: string - name: id dtype: string - name: content dtype: string splits: - name: train num_bytes: 102081135272.0 num_examples: 2916655 download_size: 26047978422 dataset_size: 102081135272.0 - config_name: ir_low_resource features: - name: __index_level_0__ dtype: string - name: id dtype: string - name: content dtype: string - name: size dtype: int64 splits: - name: train num_bytes: 10383382043.0 num_examples: 393988 download_size: 2464513603 dataset_size: 10383382043.0 - config_name: ir_python features: - name: id dtype: string - name: content dtype: string splits: - name: train num_bytes: 12446664464.0 num_examples: 154507 download_size: 3039297625 dataset_size: 12446664464.0 - config_name: ir_rust features: - name: __index_level_0__ dtype: string - name: id dtype: string - name: content dtype: string splits: - name: train num_bytes: 4764927851.0 num_examples: 32720 download_size: 1254786199 dataset_size: 4764927851.0 - config_name: issues features: - name: repo_name dtype: string - name: content dtype: string - name: issue_id dtype: string splits: - name: train num_bytes: 31219575534.38484 num_examples: 15549682 download_size: 16483899047 dataset_size: 31219575534.38484 - config_name: kaggle features: - name: content dtype: string - name: file_id dtype: string splits: - name: train num_bytes: 5228745262.0 num_examples: 580195 download_size: 2234440007 dataset_size: 5228745262.0 - config_name: lhq features: - name: content dtype: string - name: metadata struct: - name: difficulty dtype: string - name: field dtype: string - name: topic dtype: string splits: - name: train num_bytes: 751273849.0 num_examples: 7037500 download_size: 272913202 dataset_size: 751273849.0 - config_name: owm features: - name: url dtype: string - name: date dtype: timestamp[s] - name: metadata dtype: string - name: content dtype: string splits: - name: train num_bytes: 56294728333.0 num_examples: 6315233 download_size: 27160071916 dataset_size: 56294728333.0 - config_name: stackoverflow features: - name: date dtype: string - name: nb_tokens dtype: int64 - name: text_size dtype: int64 - name: content dtype: string splits: - name: train num_bytes: 35548199612.0 num_examples: 10404628 download_size: 17008831030 dataset_size: 35548199612.0 - config_name: wikipedia features: - name: content dtype: string - name: meta dtype: string - name: red_pajama_subset dtype: string splits: - name: train num_bytes: 21572720540.0 num_examples: 6630651 download_size: 12153445493 dataset_size: 21572720540.0 configs: - config_name: arxiv data_files: - split: train path: arxiv/train-* - config_name: documentation data_files: - split: train path: documentation/train-* - config_name: ir_cpp data_files: - split: train path: ir_cpp/train-* - config_name: ir_low_resource data_files: - split: train path: ir_low_resource/train-* - config_name: ir_python data_files: - split: train path: ir_python/train-* - config_name: ir_rust data_files: - split: train path: ir_rust/train-* - config_name: issues data_files: - split: train path: issues/train-* - config_name: kaggle data_files: - split: train path: kaggle/train-* - config_name: lhq data_files: - split: train path: lhq/train-* - config_name: owm data_files: - split: train path: owm/train-* - config_name: stackoverflow data_files: - split: train path: stackoverflow/train-* - config_name: wikipedia data_files: - split: train 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} } ```