datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
github-codereview
Code Review Dataset
A large-scale dataset of the best human-written code reviews from top GitHub repositories.
Each row captures a moment where a human code reviewer left an inline comment on a pull request, and the author subsequently modified the code in response.
The dataset also includes negative examples — code from the same PRs that passed review without comments — to help models learn when code is acceptable.
This provides a natural signal for training models to:
Generate… See the full description on the dataset page: https://huggingface.co/datasets/ronantakizawa/github-codereview.CodeReviewWithSummaryQAcodereviewercode-review-instruct-critique-revision
Dataset Card for "code-review-instruct-critique-revision"
More Information needed
CodeReviewQA 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-review-preference-pairs
Code Review Preference Pairs
Rights & intended use: legacy public research corpus / portfolio
artifact. Hosted frontier-model outputs are research-only inputs under
project policy (synthetic-factory#161):
intended_use: research_only, project_training_policy: blocked. Not
training data for any model-weight update. Machine-readable record:
rights.json.
Release status: The raw, uncurated payload is now published under
data/raw/. It is available for inspection and reproducibility… See the full description on the dataset page: https://huggingface.co/datasets/rmems/code-review-preference-pairs.swebench-codereview-benchmark-v3
SWE-bench Code Review Benchmark v3
This dataset contains 7 benchmark splits for evaluating code review models on the SWE-bench task.
Dataset Summary
Total instances: 3500
Total resolved: 801 (22.9%)
Splits: 7 (3 main + 4 weak models)
Version: 3.0.0
Created: 2026-05-03
Splits
Split
Instances
Resolved
Resolve Rate
Model
glm5_500_v3
500
361
72.2%
openai/GLM-5-FP8
qwen3_coder_30b_500_v3
500
235
47.0%
Qwen/Qwen3-Coder-30B-A3B-Instruct… See the full description on the dataset page: https://huggingface.co/datasets/ruoyu001/swebench-codereview-benchmark-v3.code-review-bench
Code Review Bench
A paired online-offline benchmark for AI code review.
Splits
online — Stratified sample of 1,135 bot-reviewed PRs, scraped from open-source Github repositories and scored by the online benchmark (15 tools, Feb–Apr 2026).
offline — 136 expert-curated golden issues across 50 PRs (5 repositories).
Provenance
The offline golden issues extend the 50-PR benchmark originally created by Greptile (2025) and refined by Augment (2025). Our… See the full description on the dataset page: https://huggingface.co/datasets/code-review-bench/code-review-bench.code-review-lab
CodeReview laboratory changes
Synthetic Python before/after pairs and unified diffs for the CodeReview change-scoped secure-review demo. Seed 24.
Organization dataset and collection are public. Live Gradio will be alirezaaminzadeh/code-review and the organization card AriaAICompany/code-review after the daily Space-creation cap resets (scripts/publish.py). Runnable Space source is stored in demo/. Collection: Aria AI — Cybersecurity.
This is fixture data (level 1). The snippets… See the full description on the dataset page: https://huggingface.co/datasets/AriaAICompany/code-review-lab.code-review-instruct-critique-revision-pythoncode-reviewA Scrape of the codereview stack exchange, good for high quality code
code-review
CODE_REVIEW
A preference dataset for CODE_REVIEW, harvested from real, human-labelled sources and curated by an automated harvesting harness with an LLM quality gate.
Format
Standard preference / DPO schema — each row:
column
meaning
prompt
the request (originally code)
chosen
the human-preferred response
rejected
a worse response to the same prompt
source
the dataset/URL the row was harvested from
Splits
80/10/10 train /… See the full description on the dataset page: https://huggingface.co/datasets/316usman/code-review.codereview-bench
CodeReview-Bench
A benchmark for evaluating models on two code review tasks, curated from ronantakizawa/github-codereview.
Tasks
1. Code Editing
Given code and a reviewer comment, apply the requested change.
Input: before_code, reviewer_comment, language, diff_context
Target: after_code
from datasets import load_dataset
ds = load_dataset("ronantakizawa/codereview-bench", "code-editing")
example = ds["test"][0]
prompt = f"""Apply the following review comment… See the full description on the dataset page: https://huggingface.co/datasets/ronantakizawa/codereview-bench.github-codereview-dataset
Github-Codereview-Dataset
Made with ❤️ using 🦥 Unsloth Studio
github-codereview-dataset was generated with Unsloth Recipe Studio. It contains 10,000 generated records.
🚀 Quick Start
from datasets import load_dataset
# Load the main dataset
dataset = load_dataset("manishsaini1/github-codereview-dataset", "data", split="train")
df = dataset.to_pandas()
📊 Dataset Summary
📈 Records: 10,000
📋 Columns: 23
📋 Schema & Statistics… See the full description on the dataset page: https://huggingface.co/datasets/manishsaini1/github-codereview-dataset.stackexchange-codereview-sandboxes-traces-terminus-2terminal_bench_2_a1_stackexchange_codereview_20260711_155918stackexchange-codereview-sandboxes_glm_4.7_traces_jupiterstackexchange_codereviewb2_code_fasttext_pos_codeforces_neg_codereviewstackexchange-codereview-sandboxescode_review_generationCodeReview-Comments-Raw
CodeReview-Comments-Raw
Raw code review comments extracted from The-Stack-Dedup subset.
Description
This dataset contains raw code review comments extracted from code repositories for training AI models on code review tasks.
Source
This dataset is derived from bigcode/the-stack-dedup.
Acknowledgments
This dataset acknowledges The Stack.
terminal_bench_2_stackexchange_codereview_sandboxes_traces_terminus_2_overwrite6d215e47dev_set_v2_a1_stackexchange_codereview_20260710_112156eval-fsr-a1-stackexchange-codereview-swe-r378-rf0710-tracesCode-Review-Assistant
Dataset Card for Code Review Assistant Training Dataset
Dataset Description
Overview
This is the training split of the Code Review Assistant Dataset - a comprehensive synthetic dataset designed for fine-tuning AI models in Python code review, security analysis, and code quality assessment.
Dataset Summary
Curated by: Alen Philip
Language: English (with Python code examples)
License: cc-by-nc-4.0
Total Examples: 13,670
Purpose: Training data for code… See the full description on the dataset page: https://huggingface.co/datasets/alenphilip/Code-Review-Assistant.reasoning-sft-github-codereview
reasoning-sft-github-codereview
Converted version of ronantakizawa/github-codereview, filtered to 76,689 high-quality rows (quality_score >= 0.75, excluding none comment type).
Nothing fancy, just reformatted the columns into a standard messages format for SFT/reasoning training. No content was modified or regenerated.
Format
Each row has three columns:
input — list of dicts with role and content (system prompt + user turn containing the reviewer comment and original… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-github-codereview.terminal_bench_2_a1_stackexchange_codereview_20260406_035458code-review-benchmarkcode-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.