datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
debugtest3
DebugTestsuper-debug-v3
super-debug-v3
super-debug-v3 is a synthetic dataset of grounded software-debugging trajectories generated with hen, a stateful long-horizon AI coding agent for C/C++ projects.
This is the third version of super-debug. Compared with super-debug-v2, which focused on SimpleC/compiler debugging runs, v3 includes synthesized data across the newer hen/Projects project set:
clcalc
math3d
mini2d_tilegame
ocr8
poseblend
rigid2d
sgps
simplec
tinyvm
The default config is the… See the full description on the dataset page: https://huggingface.co/datasets/georvn7/super-debug-v3.DebugBench
Dataset Summary
DebugBench is a Large Language Model (LLM) debugging benchmark introduced in the paper DebugBench: Evaluating Debugging Capability of Large Language Models. We collect code snippets from the LeetCode community and implant bugs into source data with GPT-4. The project is also open-sourced as a GitHub repository.
It consists of 4,253 instances.
It covers four major bug categories and 18 minor types.
It includes C++, Java, and Python instances.
It contains three… See the full description on the dataset page: https://huggingface.co/datasets/Rtian/DebugBench.super-debug-v2
super-debug-v2
super-debug-v2 is a synthetic dataset of grounded software-debugging trajectories generated with hen, a stateful long-horizon AI coding agent for C/C++ projects.
This is the second version of super-debug. Compared with super-debug-v1, this release is generated from three full-suite debugging runs. The previous release kept trajectories that passed only the first three validation steps; this version keeps trajectories from runs that pass the full hen/SimpleC/tests… See the full description on the dataset page: https://huggingface.co/datasets/georvn7/super-debug-v2.cached-activationsrag-retrieval-debug-trajectories
Rag Retrieval Debug Trajectories
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… See the full description on the dataset page: https://huggingface.co/datasets/rmems/rag-retrieval-debug-trajectories.observability-debug-trajectories
Observability Debug Trajectories
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… See the full description on the dataset page: https://huggingface.co/datasets/rmems/observability-debug-trajectories.fable-5-coding-and-debugging-traces-synthetic-corrections
Model Synthetic Corrections
1 TRAJECTORIES · 2 TRAINING ROWS · 16 kB
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Synthetic Corrections companion dataset. The original dataset is greghavens/fable-5-coding-and-debugging-traces. These are narrowly, synthetically corrected, independently re-judged traces that never passed in the original dataset.
Behavior-preserving instruction-following… See the full description on the dataset page: https://huggingface.co/datasets/greghavens/fable-5-coding-and-debugging-traces-synthetic-corrections.kimi-k3-coding-and-debugging-traces
Kimi K3 Coding & Debugging Agent Traces
Generated by moonshiner — an open harness for
distilling verified, model-attested agentic coding traces.
Real, end-to-end agentic coding trajectories produced by
moonshotai/kimi-k3 driving the pi coding-agent runtime over
openrouter, at max reasoning. Each trajectory solves a concrete
repair or build task in a real repository — reading, editing, and running code
with tools — and is published only after its work verifiably passes —… See the full description on the dataset page: https://huggingface.co/datasets/gbeck/kimi-k3-coding-and-debugging-traces.super-debug-v1
super-debug-v1
super-debug-v1 is a synthetic dataset of grounded software-debugging trajectories generated with hen, a stateful long-horizon AI coding agent for C++ projects.
It is designed as a Hugging Face-friendly dataset repo with three complementary views:
a single consolidated Hen-native training file, super-debug-v1.jsonl
protocol-stripped abstract debugging views under abstract/
a browsable raw/ directory containing the underlying trajectory and distillation artifacts… See the full description on the dataset page: https://huggingface.co/datasets/georvn7/super-debug-v1.SQLFlow
Text2SQL-Flow Dataset Repository
This repository contains the SQLFlow dataset.
The SQLFlow dataset is a large-scale, high-quality collection of semantically valid and structurally diverse Text-to-SQL examples, generated using a comprehensive SQL-aware data augmentation framework.
For more details, please visit the GitHub repository:🔗 https://github.com/TechNomad-ds/Text2SQL-Flow
python_debugging
Python Debugging
A synthetic instruction-tuning dataset for training AI models to identify and fix bugs in Python code.
Dataset Summary
Field
Value
Entries
75
Format
input / output pairs
Language
English
Topic
Finding and fixing bugs in Python code
Synthetic
Yes, generated with DeepSeek
License
MIT
Dataset Description
Each entry presents a snippet of Python code containing a deliberate bug, along with a corrected version… See the full description on the dataset page: https://huggingface.co/datasets/creeperdatasets/python_debugging.intern-debug-lerobot
debug: robot demonstrations
Instruction: Nest the three paper cups together into a single stack.
LeRobot v3.0 dataset: 51 episodes, 43257 frames, nominal 30 Hz.
Robot schema: intern_gello_7dof_robotiq. Original source recordings are retained by the owner.
Use
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("cloudfan/intern-debug-lerobot", video_backend="torchcodec")
sample = dataset[0]
print(sample["task"]… See the full description on the dataset page: https://huggingface.co/datasets/cloudfan/intern-debug-lerobot.code-debugging-sft-50k
Code Debugging SFT (50K)
50,000 ShareGPT-format conversations where the user presents buggy code and the assistant provides root-cause analysis and a corrected solution. Covers Python, JavaScript, Go, TypeScript, and SQL across 14 bug categories.
Motivation
Debugging is one of the most frequent developer tasks — and one of the hardest to train. Most coding datasets focus on writing code from scratch. This dataset trains models to:
Identify the precise root cause… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/code-debugging-sft-50k.chinese-lips-longform-debug
Chinese-LiPS Long-Form (zh long streaming speech)
Reconstructed continuous long-speech streams from
BAAI/Chinese-LiPS, for
slide-aware / streaming speech-translation development and evaluation. Each
source video (one speaker, one scripted lecture with slides) was released as
pre-segmented clips; here they are re-joined into the full talk.
Two variants of the same 3 talks (~97 min speech total):
config
how segments are placed
use
orig_timeline
at their original session… See the full description on the dataset page: https://huggingface.co/datasets/gavinlaw/chinese-lips-longform-debug.origen_dataset_debug
OriGen: Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection
Introduction
OriGen is a fine-tuned lora model designed for Verilog code generation. It is trained on top of DeepSeek Coder 7B using datasets generated from code-to-code augmentation and self-reflection. The datasets can be found in the origen_dataset_instruction.
OriGen_Fix is a fine-tuned lora model designed for fixing syntax errors in Verilog code. It is trained based on OriGen… See the full description on the dataset page: https://huggingface.co/datasets/henryen/origen_dataset_debug.debugbench
DebugBench
This dataset packages the DebugBench LLM debugging-capability benchmark published by THUNLP,
reformatted into a single data.jsonl file with language and category fields identifying the
programming language and bug-shard of each record.
Source
Official repository: thunlp/DebugBench (benchmark/ folder)
Official Hugging Face mirror (data source per the repo's own README):
Rtian/DebugBench
Retrieved: 2026-09-17, from the main branch of the repository… See the full description on the dataset page: https://huggingface.co/datasets/IDENER/debugbench.fable-5-coding-and-debugging-traces-synthetic
Model Synthetic Corrections
1 TRAJECTORIES · 2 TRAINING ROWS · 16 kB
Generated by moonshiner — an open harness for
distilling verified instruction-following, tool-use, and agentic coding traces.
Synthetic Corrections companion dataset. The original dataset is greghavens/fable-5-coding-and-debugging-traces. These are narrowly, synthetically corrected, independently re-judged traces that never passed in the original dataset.
Behavior-preserving instruction-following… See the full description on the dataset page: https://huggingface.co/datasets/11-47/fable-5-coding-and-debugging-traces-synthetic.feature-flag-debug-trajectories
Feature Flag Debug Trajectories
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… See the full description on the dataset page: https://huggingface.co/datasets/rmems/feature-flag-debug-trajectories.stockfish-debug
Dataset Card for stockfish-debug
See my blog post for additional details.
Columns
The datase contain the following columns:
fen: The FEN string of the board.
move: The move that was played.
result: The result of the game (with "-" for unfinished games).
Data details
Pre-processing of the Stockfish games provided by BlueSunflower/chess_games_base.
Code used:
import jsonlines
import chess
import tqdm
def preprocess_games(in_path, out_path):
with… See the full description on the dataset page: https://huggingface.co/datasets/yp-edu/stockfish-debug.codeq-debugbench-dpo-pairs
codeq-debugbench-dpo-pairs
Self-generated preference pairs used to train the CodeQ iterative DPO
pipeline on top of Qwen/Qwen2.5-Coder-7B-Instruct. Each pair consists of
a chosen and rejected response to a DebugBench debugging prompt, where
preferences are derived from MCTS rollouts scored by a unit-test verifier.
Files
File
Rows
Description
round1.jsonl
1515
Raw Round 1 preference pairs (reference = base model).
round1_filtered.jsonl
936
Round 1 after… See the full description on the dataset page: https://huggingface.co/datasets/tathadn/codeq-debugbench-dpo-pairs.adaption-code-debug-and-refine
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-code_debug_and_refine
This dataset contains multi-turn dialogues where users present coding problems, mathematical calculations, or logic puzzles, and assistants provide initial solutions followed by refinements based on new constraints or edge cases. The content covers diverse domains including graph algorithms, chemistry, finance, and statistics, with a strong emphasis on debugging… See the full description on the dataset page: https://huggingface.co/datasets/Azfarhashmi/adaption-code-debug-and-refine.Code_Debugging_QA
Code Debugging Q&A Dataset
By dmeldrum6
A curated dataset of 1,073 question-and-answer pairs covering common debugging scenarios across Python, JavaScript, SQL, and Bash. Designed for fine-tuning and instruction-tuning language models on code debugging tasks.
Dataset Summary
Each pair presents a realistic bug symptom as a question and a structured answer containing:
A buggy code block demonstrating the problem
A corrected code block showing the fix
A… See the full description on the dataset page: https://huggingface.co/datasets/kalaiarasan27/Code_Debugging_QA.C-Language-Chat-Debug-Multiturn-Zh约 1300 条 C 语言 场景的 user - assistant 多轮对话。每段对话已经组织成了单行的格式。一条样例如下：
{
"id": 1045,
"conversation": [
{
"user": "你好，AI助手。我最近在写一个C语言程序，但是遇到了一些问题，希望你能帮我检查一下。",
"assistant": "你好，我很乐意帮助你。请把你的代码发给我，我会尽快检查并给出建议。"
},
{
"user": "好的，这是我的代码。这段代码的主要功能是计算斐波那契数列的前n项。",
"assistant": "让我看一下......嗯，这里有一个小错误。在第10行，你应该使用`++i`而不是`i++`来递增i的值。修改后的代码应该是这样的\\n```c\\nfor (int i = 0; i < n; ++i) {\\n if (i == 0 || i == 1) {\\n… See the full description on the dataset page: https://huggingface.co/datasets/Mxode/C-Language-Chat-Debug-Multiturn-Zh.dpo_debugdebug_divas45
Colloquial Tamil Translation Dataset
Description
This dataset consists of English sentences and their colloquial Tamil translations. It is designed to train and evaluate machine learning models for English-to-Tamil translation in an informal, conversational tone.
The dataset is structured to help in fine-tuning language models for translation tasks that require a natural and spoken Tamil output, rather than formal literary translations.
Dataset Structure
Each… See the full description on the dataset page: https://huggingface.co/datasets/anitha2520/debug_divas45.self_evolving_self_debugging_250_implementations-2dfm8-synthetic-code-debugging
Code Generation and Debugging
Synthetic DFM8 training data generated with Gemma 4 31B and filtered by deterministic checks plus a Gemma 4 31B judge.
Schema
Rows are JSONL chat records:
{"messages": [{"role": "user", "content": "..."}, {"role": "assistant", "content": "..."}]}
Tool-calling rows may also include a top-level tools list and assistant tool_calls.
Counts
accepted rows: 340711
generated rows seen: 4800000
audit rows seen: 4580233… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm8-synthetic-code-debugging.requests_debug