datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rayst3rbartowski-imatrix-v5-semantic
Bartowski iMatrix Calibration v5 (Semantic Chunking)
A processed version of bartowski's v5 imatrix calibration data using semantic boundary detection optimized for the v5 data structure.
Dataset Summary
Metric
Value
Total samples
2,075
Chunking method
V5-optimized semantic boundary detection
Chunk size
200+ characters (no upper limit, preserves document integrity)
Languages
English, German, Spanish, French, Italian, Swedish, Russian, Arabic, Chinese… See the full description on the dataset page: https://huggingface.co/datasets/lemon07r/bartowski-imatrix-v5-semantic.Leo__bart-large__1645784880GEM__bart_base_schema_guided_dialog__1645547915aplikacje-prawnicze-mcq
Polish Legal Apprenticeship Entrance Exams — adwokacka/radcowska, notarialna, komornicza (2007–2025)
Native-Polish, single-choice (A/B/C) legal MCQ benchmark built from the official entrance
examinations for the Polish legal apprenticeships, published by the Ministry of Justice:
adwokacka + radcowska (advocate + legal counsel — a single shared test from 2009 on;
two separate exams in 2007),
notarialna (notary),
komornicza (court-enforcement officer / bailiff).
Each item… See the full description on the dataset page: https://huggingface.co/datasets/bartoszkobylinski1/aplikacje-prawnicze-mcq.SWE-Repair
Dataset Summary
SWE-Repair is a curated subset of SWE-Bench, containing 204 single-function Python bugs from real-world GitHub repositories. Each example includes a buggy implementation and its corresponding problem statement.
Supported Tasks
Program Repair: Fixing bugs in Python functions
Code Generation: Generating correct implementations from buggy code
Dataset Structure
Each row contains:
instance_id: Unique identifier for the task (in format:… See the full description on the dataset page: https://huggingface.co/datasets/barty/SWE-Repair.tigerbot-wiki-qa-bart-en-10kTigerbot 英文wiki类的问答数据
原始来源：https://huggingface.co/datasets/michaelthwan/oa_wiki_qa_bart_10000row
Usage
import datasets
ds_sft = datasets.load_dataset('TigerResearch/tigerbot-wiki-qa-bart-en-10k')
EvalRepair-Java
Dataset Summary
EvalRepair-Java is a benchmark for evaluating Java program repair performance, derived from HumanEval. It contains 163 single-function repair tasks, each with a buggy implementation and its corresponding fixed version.
Supported Tasks
Program Repair: Fixing bugs in Java functions
Code Generation: Generating correct implementations from buggy code
Dataset Structure
Each row contains:
task_id: Unique identifier for the task (same as HumanEval)… See the full description on the dataset page: https://huggingface.co/datasets/barty/EvalRepair-Java.bartowski-imatrix-v3-semantic
Bartowski iMatrix Calibration v3 (Semantic Chunking)
A processed version of bartowski's v3 imatrix calibration data using semantic boundary detection in attempt to create coherent, non-overlapping samples.
Dataset Summary
Metric
Value
Total samples
168
Chunking method
Semantic boundary detection
Target chunk size
~2048 characters
Languages
English, German, Spanish, French, Italian, Swedish, Russian, Arabic, Chinese
Source Data
The… See the full description on the dataset page: https://huggingface.co/datasets/lemon07r/bartowski-imatrix-v3-semantic.EvalRepair-Cpp
Dataset Summary
EvalRepair-C++ is a benchmark for evaluating C++ program repair performance, derived from HumanEval. It contains 164 single-function repair tasks, each with a buggy implementation and its corresponding fixed version.
Supported Tasks
Program Repair: Fixing bugs in C++ functions
Code Generation: Generating correct implementations from buggy code
Dataset Structure
Each row contains:
task_id: Unique identifier for the task (same as HumanEval)… See the full description on the dataset page: https://huggingface.co/datasets/barty/EvalRepair-Cpp.D4J-Repair
Dataset Summary
D4J-Repair is a curated subset of Defects4J, containing 371 single-function Java bugs from real-world projects. Each example includes a buggy implementation, its corresponding fixed version, and unit tests for verification.
Supported Tasks
Program Repair: Fixing bugs in Java functions
Code Generation: Generating correct implementations from buggy code
Dataset Structure
Each row contains:
task_id: Unique identifier for the task (in format:… See the full description on the dataset page: https://huggingface.co/datasets/barty/D4J-Repair.Simon1997__bart-base_original_cacapo__1678442415
GEM Submission
Submission name: BART-base_Original_CACAPO
Simon1997__bart-base_original_cacapo__1678442337
GEM Submission
Submission name: BART-base_Original_CACAPO
arxiv_jsonSimon1997__bart-base_original_cacapo__1678442552
GEM Submission
Submission name: BART-base_Original_CACAPO
Simon1997__bart-base_original_cacapo__1678442469
GEM Submission
Submission name: BART-base_Original_CACAPO
glossa-bidirectional-t5-bartDBSimon1997__bart-base_original_cacapo__1678442649
GEM Submission
Submission name: BART-base_Original_CACAPO
Simon1997__bart-base_original_cacapo__1678442421
GEM Submission
Submission name: BART-base_Original_CACAPO
agentkbart_datalit2vec-tldr-bart-dataset
Lit2Vec TL;DR Chemistry Dataset
Summary
The Lit2Vec TL;DR Chemistry Dataset is a curated collection of 19,992 chemistry research abstracts paired with short, TL;DR-style abstractive summaries.It was created to support research in scientific text summarization, semantic indexing, and domain-specific knowledge graph construction.
Unlike generic summarization datasets, this corpus is:
Legally reusable → all abstracts are sourced from CC-BY licensed publications… See the full description on the dataset page: https://huggingface.co/datasets/Bocklitz-Lab/lit2vec-tldr-bart-dataset.test_dataset
test purpose
barts2018PoftheC_Lettersalgorithmic_taskstrain_pop_valet_no_wrong_doc