datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
appliancedb-error-codes-repair-database
ApplianceDB: Home Appliance Error Codes & Ranked Repairs
Full dataset: appliancedb.dataengineered.io · $99 one-time (Repair Intelligence Snapshot: commercial licence + SQLite and Parquet builds; the same rows as this sample) → Buy on Stripe · the same sample on Kaggle
Relational database mapping 438 home-appliance error codes across 13 brands and 26 (brand, appliance-type) pairs to 288 ranked repair procedures with DIY difficulty tiers. Every code is identified by its… See the full description on the dataset page: https://huggingface.co/datasets/Ichlibitiche/appliancedb-error-codes-repair-database.hvac-error-codes
HVAC Bench Error Code Dataset
Error codes from HVAC equipment sold in the United States, United Kingdom, and Europe, as published by HVAC Bench. Each record gives the manufacturer, the code, the product family the definition applies to, a plain-language meaning, the checks an owner can safely make, the point at which a technician is needed, and the date the definition was last checked against manufacturer documentation. Codes are specific to a product family and are not… See the full description on the dataset page: https://huggingface.co/datasets/mukarram360/hvac-error-codes.kurdish-kurmanji-grammar-error-correctionThis dataset is for developing and evaluating grammatical error correction (GEC) models,
like Grammarly, for Kurdish Kurmanji. Incorrect sentences were manually collected
from YouTube comment sections of Kurdish videos and X(Twitter) and Muzaffer Cıkay added their corrections.
The source videos are documented in the source.txt file.
Usage
from datasets import load_dataset
dataset = load_dataset("muzaffercky/kurdish-kurmanji-typo-correction", split="train")
print(dataset)
vietnamese-error-correction-corpus
Data Summary
The model is trained on a Vietnamese text error correction dataset constructed from real-world noisy inputs. The dataset contains approximately 70,000 sentence pairs and is split into training, validation, and test sets.
• Data Source: Crawled Vietnamese social media comments, reflecting informal and user-generated text.
• Annotation Method: Automatically labeled using a large language model, which generates corrected versions of noisy inputs.
• Data… See the full description on the dataset page: https://huggingface.co/datasets/yammdd/vietnamese-error-correction-corpus.ErrorRadar
ErrorRadar
This repo is designed to evaluate MLLM's capability in localizing errors in user answers.
Code : [https://anonymous.4open.science/r/Error-Radar/readme.md]Dataset : [https://huggingface.co/datasets/ErrorRadar/ErrorRadar]
Dataset Details
The file ErrorRadar_dataset.csv contains 2500 samples of the dataset.
Directly clicking the image url in huggingface web site may result in 403 Forbidden Error. Therefore we recommend to paste the link into the search bar… See the full description on the dataset page: https://huggingface.co/datasets/ErrorRadar/ErrorRadar.errores-registro-horario-espana
Errores frecuentes en el registro horario y por qué incumplen (España)
13 errores concretos en la llevanza del registro de jornada, cada uno con la norma que incumple, cómo se detecta y cómo se corrige. No es una lista de buenas prácticas: cada fila describe un fallo real y verificable.
Publicado por Nucleo360, software de recursos humanos para pymes españolas.
Por qué este conjunto de datos
Casi ninguna empresa es sancionada por no tener registro horario. Se… See the full description on the dataset page: https://huggingface.co/datasets/Nucleo360/errores-registro-horario-espana.epl-inplay-quad-fatigue-sub-error-collapse-v0.1EPL In-Play Quad Fatigue Substitution Error Collapse v0.1
What this dataset is
You test whether a model can detect late-game defensive collapse.
Each row represents a defending team state in minute 65 to 95.
Core quad coupling
Sprint intensityMinutes since last substitutionDefensive duel successError rate
The label asks
Will this team concede a goal in the next 120 seconds
Why this matters
Late goals decide matches.
Defensive collapse is usually a coupling failure between fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-fatigue-sub-error-collapse-v0.1.errored_pythonThis is a subset of the python dataset provided but Ailurophile on Kaggle.
Important:Errors were introduced on purpose to try to test a sort of "specialized masking" in a realistic way.
Goal:The goal is to create a specialized agent, and add it to a chain with at least one other agent that generates code, and can hopefully "catch" any errors.
Inspiration:When working to generate datasets with other models, I found that even after multiple "passes" errors where still missed.
Out of curiosity… See the full description on the dataset page: https://huggingface.co/datasets/TacoPrime/errored_python.errors
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Nei]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More Information… See the full description on the dataset page: https://huggingface.co/datasets/katsukiai/errors.quantum-error-correction-failure-v0.1
quantum-error-correction-failure-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in quantum error correction regimes.
Each row represents a simplified quantum computing scenario where logical qubits are protected using error correction.
The task is to determine whether the correction mechanism remains stable or fails due to noise and correction latency.
Core stability idea
Quantum error correction works by detecting and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/quantum-error-correction-failure-v0.1.clinical-diagnostic-inference-error-amplification-mapping-v0.1What this dataset tests
How small inference errors introduced at a decision nodeamplify into downstream diagnostic distortion.
Required outputs
error entry node
inference error type
amplification factor
downstream distortion map
delay and misdiagnosis probabilities
self-correction points
prevention guardrails
rscl-error-recognition-fidelity-v0.1
What this dataset tests
Whether a system recognizes its own error when challenged.
Not whether it can produce a new answer.
Recognition first.
Why this exists
Self-correction fails early when the model:
denies the mistake
misses the actual error type
changes output without acknowledging why
This dataset scores the recognition step.
Data format
Each row contains:
user_task
model_initial_output
error_signal
model_acknowledgement
error_type… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/rscl-error-recognition-fidelity-v0.1.parlabe-error-correccio-traduccions-1m
Dataset sintètic de parelles error-correcció (1M)
Aquest dataset conté 1.111.000 parelles de frases en format:
text_erroni,text_correcte
Està dissenyat per a l'entrenament de models de correcció gramatical i semàntica en català.
Com s'ha generat?
A partir del dataset anglès C4_200M Synthetic, cada frase s'ha traduït al català dues vegades:
Frase correcta: traduïda amb softcatala/translate-eng-cat, que manté estructura i sentit correctes.
Frase errònia: traduïda amb… See the full description on the dataset page: https://huggingface.co/datasets/Oriolshhh/parlabe-error-correccio-traduccions-1m.nanbeige-ai-errors
Technical Challenge: Blind Spots of Frontier Models
This dataset was created as part of a technical challenge to identify and document the "blind spots" of a recent, moderately-sized base model. The goal was to browse models released in the last 6 months (between 0.6B and 6B parameters), select one, and systematically probe its failures to understand its limitations.
Dataset: Nanbeige4.1-3B AI Errors
This dataset contains 10 examples where the Nanbeige/Nanbeige4.1-3B… See the full description on the dataset page: https://huggingface.co/datasets/abdulrahman245/nanbeige-ai-errors.vi-error-correction-v2qwen-base-error-analysis
Qwen3.5-4B-Base Error Analysis Dataset
This dataset contains 10 diverse examples where the base language model Qwen3.5-4B-Base makes incorrect or unexpected predictions. It was created as part of an exploration of base model blind spots and failure modes.
Model Tested
Model: Qwen/Qwen3.5-4B-Base
Type: Pre-trained base model (not instruction-tuned)
Parameters: 4B
Architecture: Causal Language Model with hybrid Gated DeltaNet + Attention layers
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/ArslanMZahid/qwen-base-error-analysis.Referencing_Errors_Synthetic_EN
Synthetic Dataset for Automatic Error Correction in Referencing
This dataset includes 4,600 parallel sentences for Automatic Error Correction in referencing in German.It was synthetically created with gpt-4o-mini model according to the Institutional Guidelines of the Center for Translation Studies (CTS), University of Vienna.
Dataset Description
corrupted_sentence: the sentence containing the referencing error
clean_sentence: the correct version of the corrupted sentence… See the full description on the dataset page: https://huggingface.co/datasets/elizaveta-dev/Referencing_Errors_Synthetic_EN.vi-error-correction-2.0clinical-quad-pk-sampling-sparse-data-model-misspecification-dose-recommendation-error-v0.1Clinical Quad PK Sampling Sparse Data Model Misspecification Dose Recommendation Error v0.1
Each row is a site monthly snapshot.
Core quad
PK sampling densitySparse dataModel misspecificationDose recommendation error
Target
label_decision_error_risk_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-pk-sampling-sparse-data-model-misspecification-dose-recommendation-error-v0.1.parlabe-errors-genere-60k
Dataset d'errors de gènere en català (60.000 parelles)
Aquest dataset conté 60.000 parelles de frases amb errors de gènere, generades mitjançant un script automatitzat en Python. Cada parella està formada per:
text_erroni,text_correcte
Objectiu
Aquest conjunt de dades està pensat per entrenar models de correcció gramatical en català, amb un focus específic en la detecció i correcció d’errors de gènere:
Concordança nominal (ex: el noia → la noia)
Concordança adjectival… See the full description on the dataset page: https://huggingface.co/datasets/Oriolshhh/parlabe-errors-genere-60k.clinical-quad-site-training-protocol-complexity-error-rate-data-usability-v0.1Clinical Quad Site Training Protocol Complexity Error Rate Data Usability v0.1
Each row is a site week snapshot.
Core quad
Site training intensityProtocol complexityOperational error rateData usability
Target
label_data_collapse_next_60d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
student-performance
Student Performance Dataset
Dataset Description
This dataset contains ten million synthetically generated student performance records, designed to mimic real-world educational data at the high-school level. It includes detailed demographic, socioeconomic, academic, behavioral, and school-context features for each student, suitable for benchmarking, machine learning, educational research, and exploratory data analysis.
File Information
Split
File Name… See the full description on the dataset page: https://huggingface.co/datasets/ErrorER123/student-performance.clinical-quad-data-cut-query-backlog-database-lock-decision-error-v0.1Clinical Quad Data Cut Query Backlog Database Lock Decision Error v0.1
Each row is a data cut snapshot.
Core quad
Data cut timingQuery backlogDatabase lock pressureDecision error risk
Target
label_wrong_call_next_30d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
Errors_Mod This dataset is the result of errors found in generated ecore files by different LLMs, mainly GTP4-Turbo and Llama3-70b-Instruct.
The errors have been classified into :
Wrong Type : This can occur if the generated type is non existant or used in a wrong way
Missing declaration : this can be due to either a missing declaration like xsi or nonexistant one
Start Token : this can mostly be due to start tag <?xml ..> <ecore ..> that are missing, happens when we can't read the file or error in… See the full description on the dataset page: https://huggingface.co/datasets/VeryMadSoul/Errors_Mod.parlabe-errors-ortografia-45k
Dataset d’errors ortogràfics en català (45.000 parelles)
Aquest dataset conté 45.000 parelles de frases en format:
text_erroni,text_correcte
Està dissenyat per entrenar models de correcció ortogràfica general en català, abastant una gran varietat d’errors comuns en l’escriptura manual, digitació ràpida, ASR o OCR.
Què inclou?
Aquestes parelles cobreixen errors com:
Lletres intercanviades o repetides: Axo és una prova → Això és una prova
Omissions o afegits de caràcters:… See the full description on the dataset page: https://huggingface.co/datasets/Oriolshhh/parlabe-errors-ortografia-45k.granite-base-model-errors
Granite-1B Base Model Errors
Overview
This dataset contains 10 examples where the Granite-4.0-1B-Base language model produces incorrect or awkward outputs. Each row includes:
id: a unique identifier for each example
input: the prompt given to the model
expected_output: what the correct answer or completion should be
model_output: what the model actually produced
The dataset demonstrates common blind spots of a base causal language model, including factual errors, logic… See the full description on the dataset page: https://huggingface.co/datasets/thatgirltomiie/granite-base-model-errors.clinical-quad-temperature-excursion-cold-chain-break-potency-loss-site-dosing-error-v0.1Clinical Quad Temperature Excursion Cold Chain Break Potency Loss Site Dosing Error v0.1
Each row is a shipment to site week snapshot.
Core quad
Temperature excursionCold chain breakPotency lossSite dosing error
Target
label_site_dosing_error_next_30d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-temperature-excursion-cold-chain-break-potency-loss-site-dosing-error-v0.1.error-correction-viparlabe-errors-castellanismes-35k
Dataset de castellanismes en català (35.000 parelles)
Aquest dataset conté 35.000 parelles de frases en format:
text_erroni,text_correcte
El conjunt inclou frases amb castellanismes habituals en el català oral i escrit, generades de manera sintètica per entrenar models que detectin i corregeixin aquestes interferències.
Com s’ha generat?
Les parelles han estat generades mitjançant:
API de GPT per introduir errors de castellanismes de forma natural
Filtratge automàtic… See the full description on the dataset page: https://huggingface.co/datasets/Oriolshhh/parlabe-errors-castellanismes-35k.Qwen3.5-0.8B-Base-error-analysis
Qwen3.5-0.8B-Base Error Analysis Dataset
Model Tested
Model: Qwen/Qwen3.5-0.8B-Base
Model Type: Base / Pretrained Causal Language Model
Parameters: 0.8B
Architecture: Causal Language Model with Vision Encoder (Gated Delta Networks + MoE)
Release Date: February 2026
License: Apache 2.0
Dataset Description
This dataset contains 10 input prompts where Qwen/Qwen3.5-0.8B-Base produced incorrect, incomplete, or hallucinated outputs. The prompts were designed… See the full description on the dataset page: https://huggingface.co/datasets/AhsanShahid/Qwen3.5-0.8B-Base-error-analysis.