datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CodeReviewWithSummaryQAcodereviewerCodeReviewQA CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models
The task of automated code refinement aims to automate the developer's perspective in resolving an actionable code review comment provided by a reviewer.
This is a generative task, where the LLM is required to revise a pre-review code submission with respect to the natural language code review comment to produce an intended post-review code revision.
CodeReviewQA further breaks down this generative task… See the full description on the dataset page: https://huggingface.co/datasets/Tomo-Melb/CodeReviewQA.code-reviewA Scrape of the codereview stack exchange, good for high quality code
korean_code_reviews_from_githubgordon-ramsay-code-review-v2
Gordon Ramsay Code Review & Auditor Corpus v2 (dcmutlu/gordon-ramsay-code-review-v2)
A high-density synthetic dataset of 10,000 multi-turn code review pairs designed to fine-tune open-weight reasoners (specifically Qwen2.5-Coder-7B-Instruct) into Chef Gordon Ramsay: Sovereign Executive Code Auditor and Supreme Software Gastronomer.
🍳 Dataset Overview
This dataset merges rigorous computer science diagnostics (Abstract Syntax Tree inspection, concurrency lifecycle… See the full description on the dataset page: https://huggingface.co/datasets/dcmutlu/gordon-ramsay-code-review-v2.gordon-ramsay-code-review
gordon-ramsay-code-review
Autonomous synthetic pretraining dataset synthesized by JESUS Sovereign Forge.
Synthesized via JESUS Sovereign Cloud Model Forge (hf-colab-forge) for native byte-level micro-transformers (Atom GPT) and LLM fine-tuning.
Dataset Summary
Metric
Value
Total Scenarios
500
Train Samples
450
Validation Samples
50
Total Byte Tokens
819,927
Train Tokens
737,852
Val Tokens
82,075
Vocab Size
258 (UTF-8 Bytes + BOS/PAD)… See the full description on the dataset page: https://huggingface.co/datasets/dcmutlu/gordon-ramsay-code-review.qwen3.8-targeted-code-review-50
Qwen3.8 Max Targeted Code Review 50
A 50-record synthetic code-review dataset generated with Qwen3.8 Max and
reviewed with ChatGPT 5.6 Sol High.
The dataset is designed around precise defect identification, especially
resisting unsupported or speculative code-review findings.
Dataset Summary
The publication artifact contains 50 unique records using the schema:
{
"user": "...",
"assistant": "..."
}
Recovered final-artifact characteristics:
records: 50
unique… See the full description on the dataset page: https://huggingface.co/datasets/TaskPuppyAI/qwen3.8-targeted-code-review-50.qwen3.8-contrastive-code-review-12
Qwen3.8 Max Contrastive Code Review 12
A 12-record synthetic contrastive code-review dataset generated with Qwen3.8
Max and reviewed with ChatGPT 5.6 Sol High.
The dataset combines direct code review, proposed-finding adjudication, and
review rewriting in a compact set intended to train precise, evidence-grounded
review behavior.
Dataset Summary
The publication artifact contains 12 unique records using the schema:
{
"instruction": "...",
"input": "..."… See the full description on the dataset page: https://huggingface.co/datasets/TaskPuppyAI/qwen3.8-contrastive-code-review-12.dl4se-code-review-datasetlunamax-multilingual-code-review-50
LunaMax Multilingual Code Review 50
A 50-record synthetic multilingual code-review dataset generated with ChatGPT LunaMax.
Every record is a code-review task in user / assistant format. The set spans multiple languages and review scenarios, including correctness, debugging, API usage, security, and implementation behavior.
Dataset Size
Metric
Count
Final records
50
Unique records
50
Fresh GPT-5.6 Sol audit coverage
50
Accepted unchanged
48… See the full description on the dataset page: https://huggingface.co/datasets/TaskPuppyAI/lunamax-multilingual-code-review-50.arabic-english-code-switching-review-annotations
Review Annotations for Arabic-English Code-Switching Speech
This metadata-only dataset publishes review decisions and transcript-correction deltas for MohamedRashad/arabic-english-code-switching. It contains no human audio, no local file paths, no raw review notes, and no copies of unchanged upstream transcripts.
The annotations are pinned to upstream revision 4a3bffc45219c35949470de32b8d4cb328b0ce11 and join by upstream_row_index.
Coverage and outcomes
The… See the full description on the dataset page: https://huggingface.co/datasets/abdo1819/arabic-english-code-switching-review-annotations.code-review-dataset-ja
Japanese Code Review Dataset (500 Samples)
A dataset of 500 code review pairs (buggy code + fixed code) with Japanese review comments. Designed for training and evaluating code review assistance models.
Total samples: 500
Languages: Python (220), JavaScript (136), Go (54), Rust (52), TypeScript (38)
Difficulties: Easy (135), Medium (259), Hard (106)
Bug types: Logic Error (120), Null Pointer (81), Off-by-One (80), Edge Case (77), Type Error (60), Security (42), Performance (40)… See the full description on the dataset page: https://huggingface.co/datasets/gram-chan-jp/code-review-dataset-ja.react_native_code_review-reasoning-SFTcode-review-findings-samples
Code Review Findings Samples
Curated synthetic examples for evaluating automated code review pipelines — especially the
AI Code Reviewer MCP stack built with
Qwen3.6-27B.
Each row contains a short code snippet, the analysis type, and a structured JSON output that
matches the review contract used by ImTamsi/qwen3.6-27b-code-reviewer.
Dataset structure
Column
Description
id
Stable sample identifier
analysis_type
review, bugs, security, performance… See the full description on the dataset page: https://huggingface.co/datasets/ImTamsi/code-review-findings-samples.code-review-dpo-3k
Code Review DPO Pairs (3K)
DPO preference pairs for training LLMs to produce specific, actionable, educational code reviews.
Dataset Description
3,000 preference pairs across 4 programming languages:
Language
Examples
Python
~64%
JavaScript
~12%
TypeScript
~12%
Go
~12%
8 review scenarios covering real-world code quality issues:
SQL injection & security vulnerabilities
XSS via innerHTML
Hardcoded credentials
Resource leaks (unclosed… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/code-review-dpo-3k.contextual_code_review_fullkorean_code_reviewp06-code-review-datasetai-code-review-dataset