iaroy/sgc-data

nanochat pretraining corpus

Text for pretraining a Python and C++ code model from scratch: 178,396,088 documents from 18 sources. Every text has LF line ends and no byte-order mark; every Python file parses as Python 3, repaired from Python 2 where it did not; exact copies are removed across all sources. Train rows sharing a 10-gram of whitespace-separated words with a prompt or reference program of the scored benchmarks (HumanEval+, MBPP+, MultiPL-E's HumanEval and MBPP in C++, HumanEval-X C++, HumanEval infilling) are removed; decontamination.json lists each (shard, row before removal, benchmark tasks).

Layout

One folder per source, each with train/ and val/ Parquet shards. Validation holds 1% of each source: whole repositories in the repository folders (stack_edu_*, ultradata_stack_v3_l2_*, ultradata_code_l2_*) and codexglue_python, whole problems in codeforces_cots, documents elsewhere. A repository folder's shard holds whole repositories, each cut into samples of files that import one another (sample); any other folder's train rows are in id order, so its leading shards are a uniform sample.

Schema

Column	Meaning
content	the document's text
repo_name	its GitHub repository, owner/name
relative_path	the file's path in its repository
sample	within a shard, files sharing a number import one another; they are consecutive, in dependency order
id	the SHA-1 of content
language	the code's language, Python or C++
problem_id	the Codeforces problem

Folders

Folder	Contents	Columns	Source	Train rows	Val rows
stack_edu_python	GitHub Python files filtered for educational value	repo_name, relative_path, content, sample	HuggingFaceTB/stack-edu	24,469,760	242,463
stack_edu_cpp	GitHub C++ files filtered for educational value	repo_name, relative_path, content, sample	HuggingFaceTB/stack-edu	16,072,575	157,572
ultradata_stack_v3_l2_python	GitHub Python files, quality-filtered	repo_name, relative_path, content, sample	openbmb/UltraData-Stack-v3-L2	17,440,055	183,818
ultradata_stack_v3_l2_cpp	GitHub C++ files, quality-filtered	repo_name, relative_path, content, sample	openbmb/UltraData-Stack-v3-L2	12,365,009	122,010
ultradata_code_l2_python	GitHub Python files, quality-filtered	repo_name, relative_path, content, sample	openbmb/UltraData-Code	41,954,868	425,751
ultradata_code_l2_cpp	GitHub C++ files, quality-filtered	repo_name, relative_path, content, sample	openbmb/UltraData-Code	13,142,301	121,601
ultradata_code_l3_python	synthetic Python exercises: a task, then its solution	id, content, language	openbmb/UltraData-Code	3,833,629	39,820
ultradata_code_l3_cpp	synthetic C++ exercises: a task, then its solution	id, content, language	openbmb/UltraData-Code	4,279,369	43,356
nemotron_rewriting_python	GitHub Python files rewritten by an LLM (Qwen3-32B)	id, content, language	nvidia/Nemotron-Pretraining-Code-v2	18,020,706	182,625
nemotron_transpilation_cpp	GitHub Python files transpiled into C++ by an LLM (Qwen3-32B)	id, content, language	nvidia/Nemotron-Pretraining-Code-v2	5,125,846	51,878
codexglue_python	Python functions with their docstrings (CodeSearchNet)	id, repo_name, content, language	google/code_x_glue_ct_code_to_text	249,418	1,795
ultradata_math_l3_qa	synthetic mathematics: questions and answers	id, content	openbmb/UltraData-Math	1,073,272	10,842
ultradata_math_l3_conversation	synthetic mathematics: conversations	id, content	openbmb/UltraData-Math	667,967	6,714
ultradata_math_l3_multi_style	synthetic mathematics: varied styles	id, content	openbmb/UltraData-Math	678,935	6,839
ultradata_math_l3_textbook_exercise	synthetic mathematics: textbook exercises	id, content	openbmb/UltraData-Math	1,029,231	10,506
codeforces_cots	Codeforces problems with finished DeepSeek-R1 reasoning traces and Python or C++ solutions	id, problem_id, content	open-r1/codeforces-cots	22,450	225
kaggle_notebooks	Kaggle notebooks in Markdown: title, dataset description, the notebook as a Python script	id, content, language	HuggingFaceTB/issues-kaggle-notebooks	573,674	5,815
climbmix	English web text	id, content	karpathy/climbmix-400b-shuffle	15,625,499	157,894

Tokenizer

tokenizer/: the byte-level BPE vocabulary the nanochat model was trained with, tokenizer.tiktoken (each token's bytes in base64 and its rank) and tokenizer.pattern (the pre-tokenizer's split pattern).