datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CodeFeedback-Filtered-Instruction OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
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OpenCodeInterpreter
OpenCodeInterpreter is a family of open-source code generation systems designed to bridge the gap between large language models and advanced proprietary systems like the GPT-4 Code Interpreter. It significantly advances code generation capabilities by integrating execution and iterative refinement functionalities.
For further information and… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/CodeFeedback-Filtered-Instruction.python_code_instructions_18k_alpaca
Dataset Card for python_code_instructions_18k_alpaca
The dataset contains problem descriptions and code in python language.
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the source here.
python-codes-25k
License
MIT
This is a Cleaned Python Dataset Covering 25,000 Instructional Tasks
Overview
The dataset has 4 key features (fields): instruction, input, output, and text.It's a rich source for Python codes, tasks, and extends into behavioral aspects.
Dataset Statistics
Total Entries: 24,813
Unique Instructions: 24,580
Unique Inputs: 3,666
Unique Outputs: 24,581
Unique Texts: 24,813
Average Tokens per example: 508
Features… See the full description on the dataset page: https://huggingface.co/datasets/flytech/python-codes-25k.code-alchemy
CodeAlchemy
CodeAlchemy is a synthetic code dataset (~976.6B tokens, ~162M rows) designed for training and evaluating code language models. It consists of 5 training subsets covering a range of code-related tasks, and 2 evaluation subsets. All files are Parquet with zstd compression with on-disk size ~873 GB. Raw source files are not included due to ownership considerations and must be manually fetched as instructed below.
Dataset Statistics
Config… See the full description on the dataset page: https://huggingface.co/datasets/open-alchemy/code-alchemy.mimo-claude-code-traces-1k
MIMO Claude Code Traces
MIMO Claude Code Traces is a collection of coding-agent trajectories in a Claude Code-style environment. Each record contains a user coding task, the full multi-turn message trace, available tool schemas, assistant reasoning fields, tool calls, tool outputs, and metadata such as model name, category, duration, cost, token usage, and whether the trace used tools.
The traces were generated with mimo-v2.5-pro, MiMo's most capable model at the time of… See the full description on the dataset page: https://huggingface.co/datasets/choucsan/mimo-claude-code-traces-1k.Code-Feedback OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
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[🛠️Code]
Introduction
OpenCodeInterpreter is a family of open-source code generation systems designed to bridge the gap between large language models and advanced proprietary systems like the GPT-4 Code Interpreter. It significantly advances code generation capabilities by integrating execution and iterative refinement functionalities.
For further information and related… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/Code-Feedback.R1-Code-Interpreter-Data
R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning
Our code is based on Llama-factory/VeRL/Search-R1 for the SFT and RL training and SymBench/BIG-Bench-Hard/reasoning-gym for datasets/benchmarks of reasoning/planning tasks.
📝 Introduction
R1-Code-Interpreter is the first framework to train LLMs for step-by-step code reasoning using multi-turn supervised fine-tuning and reinforcement learning. By curating 144 diverse… See the full description on the dataset page: https://huggingface.co/datasets/yongchao98/R1-Code-Interpreter-Data.math-code-science-deepseek-r1-en
R1 Dataset Collection
Aggregated high-quality English prompts and model-generated responses from DeepSeek R1 and DeepSeek R1-0528.
Dataset Summary
The R1 Dataset Collection combines multiple public DeepSeek-generated instruction-response corpora into a single, cleaned, English-only JSONL file. Each example consists of a <|user|> prompt and a <|assistant|> response in one "text" field. This release includes:
~21,000 examples from the DeepSeek-R1-0528 Distilled Custom… See the full description on the dataset page: https://huggingface.co/datasets/Hugodonotexit/math-code-science-deepseek-r1-en.CodeX-2M-Thinking
Modotte
Note: This dataset is part of the lineup CodeX by Modotte. You can get lots of datasets in this same lineup, with the main focus on providing very high-quality datasets for model training and fine-tuning.
This dataset is fully synthetic, curated from high-quality public sources and enhanced with synthetic data generated using both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/CodeX-2M-Thinking.code_instructions_120k_alpaca
Dataset Card for code_instructions_120k_alpaca
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the original source here.
civil-code-phil
Civilex — Philippine Legal RAG & SFT Dataset
Retrieval corpus and supervised fine-tuning (SFT) data for a retrieval-augmented generation (RAG) pipeline over Philippine law: the Civil Code (Republic Act No. 386) and Supreme Court jurisprudence. Produced by the civilex-thesis research pipeline.
Dataset structure
.
├── README.md
├── civil_code_rag.jsonl # Civil Code articles + hierarchy + citation linkage
├── jurisprudence_chunks.jsonl # RAG-ready chunks… See the full description on the dataset page: https://huggingface.co/datasets/renzzyyy1028/civil-code-phil.github-code-fontend-lang
github-code fontend code
Dwonload
方式一
huggingface-cli download --resume-download LiXiang12/github-code-fontend-lang --include "*/*.zip" --repo-type dataset --local-dir github_code
方式二
进入Files and versions/data直接下载zip文件
数据统计
CodeMMLU
CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities
📌 CodeMMLU
CodeMMLU is a comprehensive benchmark designed to evaluate the capabilities of large language models (LLMs) in coding and software knowledge.
It builds upon the structure of multiple-choice question answering (MCQA) to cover a wide range of programming tasks and domains, including code generation, defect detection, software engineering principles, and much more.
📄… See the full description on the dataset page: https://huggingface.co/datasets/Fsoft-AIC/CodeMMLU.Python-Code-Solutions
Python Code Solutions
Features
1000k of Python Code Solutions for Text Generation and Question Answering
Python Coding Problems labelled by topic and difficulty
Recommendations
Train your Model on Logical Operations and Mathematical Problems Before Training it on this. This is optional for Fine Tuning 2B parameter + models.
Format the prompts in a orderly way when formatting data eg. {question} Solution: {solution} Topic: {topic}
us-legal-code
Dataset Card for United States Code (Cornell LII) — Hierarchical Sections
Dataset Summary
This dataset is purpose-built for the Prime Intellect U.S. legal evaluation environment.
This dataset contains the text of the United States Code scraped from the Legal Information Institute at Cornell Law School. Each record corresponds to a navigable section (“U.S. Code” tab only) together with its hierarchy path—title, subtitle, division, part, subpart, chapter, subchapter, and so… See the full description on the dataset page: https://huggingface.co/datasets/emre570/us-legal-code.CodeX-2M-Thinking
Modotte
Note: This dataset is part of the lineup CodeX by Modotte. You can get lots of datasets in this same lineup, with the main focus on providing very high-quality datasets for model training and fine-tuning.
This dataset is fully synthetic, curated from high-quality public sources and enhanced with synthetic data generated using both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the… See the full description on the dataset page: https://huggingface.co/datasets/txchmechanicus/CodeX-2M-Thinking.QA-Codes-perfectRust-Coder
Rust-Coder
Rust-Coder is a comprehensive text dataset designed for Rust programming language learning. It contains 12,000 unique samples focusing on distinct Rust concepts, code snippets, and explanations.
Dataset Structure
Each sample consists of:
id: A unique UUID.
instruction: A prompt or question about a Rust concept.
code: An idiomatic Rust code snippet.
explanation: A detailed explanation of the concept and code.
category: The high-level Rust category (e.g.… See the full description on the dataset page: https://huggingface.co/datasets/Convence/Rust-Coder.CodeX-7M-Non-Thinking
Modotte
Note: This dataset is part of the lineup CodeX by Modotte. You can get lots of datasets in this same lineup, with the main focus on providing very high-quality datasets for model training and fine-tuning.
This dataset is curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the most refined and extensive… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/CodeX-7M-Non-Thinking.code-verl-unified
Unified Code VERL Dataset
Overview
This dataset aggregates seven code-reasoning collections into a single VERL-formatted repository containing approximately 958,539 unique problems. The compilation prioritizes consistent extra_info structure across all source materials for seamless compatibility with VERL training frameworks.
Dataset Composition
Seven distinct splits comprise the collection:
Split
Problems
Percentage
Format
kodcode_v1_verl
434,876… See the full description on the dataset page: https://huggingface.co/datasets/sungyub/code-verl-unified.code-sante-publique
Code de la santé publique, non-instruct (2025-07-11)
The objective of this project is to provide researchers, professionals and law students with simplified, up-to-date access to all French legal texts, enriched with a wealth of data to facilitate their integration into Community and European projects.
Normally, the data is refreshed daily on all legal codes, and aims to simplify the production of training sets and labeling pipelines for the development of free, open-source language… See the full description on the dataset page: https://huggingface.co/datasets/louisbrulenaudet/code-sante-publique.CodeX-2M-Thinking
Modotte
Note: This dataset is part of the lineup CodeX by Modotte. You can get lots of datasets in this same lineup, with the main focus on providing very high-quality datasets for model training and fine-tuning.
This dataset is fully synthetic, curated from high-quality public sources and enhanced with synthetic data generated using both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of… See the full description on the dataset page: https://huggingface.co/datasets/me-aas/CodeX-2M-Thinking.CodeArena
Dataset Summary
To bridge the gap between the model-generated response and human preference, we present a rigorous human-curated benchmark CodeArena to emulate the complexity and diversity of real-world coding tasks, where 397 high-quality samples spanning 40 categories and 40 languages, carefully curated from user queries.
Data Example
An example of 'validation' looks as follows:
{
"id": "60670a8d9b1e39dd845fb1639d0d8b86",
"messages": "[{'role': 'user'… See the full description on the dataset page: https://huggingface.co/datasets/CSJianYang/CodeArena.CodeMixBench
ℹ️Dataset Card for CodeMixBench
[EMNLP'25] CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 Languages
Code-mixing is a linguistic phenomenon where multilingual speakers switch or mix two or more languages within a single utterance or conversation.
To evaluate LLMs’ comprehension of multilingual code-mixed texts, we introduce CodeMixBench, a benchmark comprising eight tasks across 18 languages.… See the full description on the dataset page: https://huggingface.co/datasets/CodeMixBench/CodeMixBench.python-code-instructions-japanese
Python Code Instructions - Japanese (18K)
Dataset Description
This dataset contains 18,612 Python programming instruction-response pairs translated to Japanese. It's designed for training language models to understand and generate Python code based on Japanese instructions.
Key Features
18,612 entries covering diverse Python programming tasks
Japanese instructions and prompts for code generation
Original English text preserved for reference
Python code… See the full description on the dataset page: https://huggingface.co/datasets/ronantakizawa/python-code-instructions-japanese.code-commande-publique
Code de la commande publique, non-instruct (2025-09-20)
The objective of this project is to provide researchers, professionals and law students with simplified, up-to-date access to all French legal texts, enriched with a wealth of data to facilitate their integration into Community and European projects.
Normally, the data is refreshed daily on all legal codes, and aims to simplify the production of training sets and labeling pipelines for the development of free, open-source… See the full description on the dataset page: https://huggingface.co/datasets/louisbrulenaudet/code-commande-publique.WestGenesis-Coder-SFT-100M
Dataset Overview
WestGenesis-Coder-Dataset is a meticulously curated coding dataset designed specifically for instruction-based model tuning and fine-tuning of existing models with enhanced code generation capabilities. This represents one of the largest and most comprehensively filtered corpora of publicly available coding data on the Hugging Face platform, with a non-thinking approach that emphasizes direct, concise code outputs for rapid model training.
Key… See the full description on the dataset page: https://huggingface.co/datasets/isthatshan/WestGenesis-Coder-SFT-100M.Flutter-Code-with-Questions-Dataset-English
🧠 Flutter Code with Questions Dataset (English)
This repository contains a high-quality dataset of Flutter-related code snippets paired with automatically generated English technical questions. The dataset is intended for use in training and fine-tuning language models, coding assistants, and educational systems focused on Flutter development.
📂 Dataset Structure
The dataset is divided into 22 CSV files, each containing 200 entries. Every entry includes:
A… See the full description on the dataset page: https://huggingface.co/datasets/NoirZangetsu/Flutter-Code-with-Questions-Dataset-English.verified-math-code-17k
Verified Math & Code, 17,000 rows
A math and code instruction dataset where every single row was mechanically checked before it was
allowed in. Not filtered by a heuristic, not scored by a model. Checked.
Two layers of verification, one per domain:
Every math answer was compared against an independent gold answer by exact, numeric and
symbolic (SymPy) comparison. If the worked solution did not arrive at the gold answer, the row
was dropped.… See the full description on the dataset page: https://huggingface.co/datasets/manifesta/verified-math-code-17k.Flutter-Code-with-Questions-Dataset-Turkish
Flutter Code with Questions Dataset (Turkish)
📦 Dataset Name: flutter_code_with_questions
Bu veri seti, Flutter framework'ü ile yazılmış kod parçacıkları ve her bir kod parçası için özel olarak üretilmiş detaylı Türkçe soruları içermektedir. Veri seti, kodların eğitim verisi olarak kullanılmasının yanı sıra, LLM (Large Language Model) tabanlı kod anlama ve soru yanıtlama modellerinin geliştirilmesinde kullanılabilir.
📁 Dataset Format
Veri dosyaları CSV… See the full description on the dataset page: https://huggingface.co/datasets/NoirZangetsu/Flutter-Code-with-Questions-Dataset-Turkish.