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311 GB
865 files
Updated about 2 months ago
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zig
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yacc
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visual-basic
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verilog
typescript
thrift
tex
tcsh
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systemverilog
stata
standard-ml
stan
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protocol-buffer
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markdown
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literate-haskell
literate-coffeescript
literate-agda
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jupyter-structured-clean-dedup
jupyter-scripts-dedup-filtered
julia
json
javascript
java-server-pages
java
isabelle
idris
html
haskell
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go
glsl
github-issues-filtered-structured
git-commits-cleaned
fortran
f-sharp
erlang
emacs-lisp
elm
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dockerfile
dart
cuda
css
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common-lisp
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README.md3.39 kB
xet
.gitattributes2.27 kB
xet
README.md

StarCoder Training Dataset

Dataset description

This is the dataset used for training StarCoder and StarCoderBase. It contains 783GB of code in 86 programming languages, and includes 54GB GitHub Issues + 13GB Jupyter notebooks in scripts and text-code pairs, and 32GB of GitHub commits, which is approximately 250 Billion tokens.

Dataset creation

The creation and filtering of The Stack is explained in the original dataset, we additionally decontaminate and clean all 86 programming languages in the dataset, in addition to GitHub issues, Jupyter Notebooks and GitHub commits. We also apply near-deduplication and remove PII, all details are mentionned in our Paper: 💫 StarCoder, May The Source Be With You

How to use the dataset

from datasets import load_dataset

# to load python for example
ds = load_dataset("bigcode/starcoderdata", data_dir="python", split="train")

GitHub issues, GitHub commits and Jupyter notebooks subsets have different columns from the rest so loading the entire dataset at once may fail, we suggest loading programming languages separatly from these categories.

jupyter-scripts-dedup-filtered
jupyter-structured-clean-dedup
github-issues-filtered-structured
git-commits-cleaned
Total size
311 GB
Files
865
Last updated
Jul 1
Pre-warmed CDN
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Contributors