Datasets:

bigcode
/

starcoder2data-extras

content stringlengths 1 15.9M
\section{Introduction} \label{sec:intro} The bending of light due to the presence of structures in its path is one very significant method to study the distribution of matter in the universe. The deflection is independent of the nature of the intervening matter, if it is dark or baryonic, and hence, this phenomenon, r...
\section{Introduction} The first detection of a baryon $\Xi^{++}_{cc}$ containing two charm quarks (i.e., having the structure {\it ccu}) has been made at CERN by LHCb collaboration last summer \cite{01}. Its mass was measured to be $3621$ MeV. The existence of such a baryon may be considered is an inevitable conseque...
\section{Introduction} In the context of complex networks, the Laplacian formalism can be used to find many useful properties of the underlying graph \cite{MERRIS1994143, Chung97, benzi, biggs93, MR1324340, Mitrovic2009}. In particular, the idea of spectral clustering is to extract some important information on the ne...
\section{Introduction} In this paper we study numerical integration of smooth functions defined over the $s$-dimensional unit cube. For an integrable function $f\colon [0,1)^s\to \mathbb{R}$, we denote the integral of $f$ by \[ I(f) := \int_{[0,1)^s}f(\boldsymbol{x})\, \mathrm{d} \boldsymbol{x}. \] We approximate $I(f)...
"\\section{Introduction.}\n\n\nIn this paper we study the evolution of a classical Newtonian particl(...TRUNCATED)
"\\section{Introduction}\nTwo codes $C,D\\subseteq{\\mathbb F}_q^n$ are said to be $x$-isometric, fo(...TRUNCATED)
"\\section{Introduction and related work}\n\\subsection*{Tournament}\nA tournament ${\\cal T}$ on $n(...TRUNCATED)
"\\section{Introduction}\n\nThe Michaelis-Menten mechanism \\cite{michaelismenten} is probably the b(...TRUNCATED)
"\\section{Introduction \\label{intro}}\nThe discrete time quantum walk (QW) was introduced as a qua(...TRUNCATED)
"\\section{Introduction}\\label{section_abstr}\r\n\r\nAssume that an $n$-tuple of positive numbers $(...TRUNCATED)

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StarCoder2 Extras

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:

Kaggle (kaggle): Kaggle notebooks from 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.
Issues (issues): processed GitHub issues, same as the Stack v1 issues.
OWM (owm): the 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.
ArXiv (arxiv): the ArXiv subset of RedPajama 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 or The Stack v2 GitHub repository.

Usage

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}
}