datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NuminaMath-1.5-RL-Verifiable
Dataset Card for NuminaMath-1.5-RL-Verifiable
Dataset Summary
NuminaMath-1.5-RL-Verifiable is a curated subset of the NuminaMath-1.5 dataset, specifically filtered to support reinforcement learning applications requiring verifiable outcomes. This collection consists of 131,063 math word problems from the original dataset that meet strict filtering criteria: all problems have definitive numerical answers, validated problem statements and solutions, and come from… See the full description on the dataset page: https://huggingface.co/datasets/nlile/NuminaMath-1.5-RL-Verifiable.24-game
Math Twenty Four (24s Game) Dataset
A comprehensive dataset for the classic math twenty four game (also known as the 4 numbers game / 24s game / Game of 24). This dataset of mathematical reasoning challenges was collected from 4nums.com, featuring over 1,300 unique puzzles of the Game of 24, with difficulty metrics derived from over 6.4 million human solution attempts since 2012.
In each puzzle, players must use exactly four numbers and basic arithmetic operations (+, -, ×, /) to… See the full description on the dataset page: https://huggingface.co/datasets/nlile/24-game.NLR-NLI
SEA Abstractive Summarization
SEA Abstractive Summarization evaluates a model's ability to read a document, identify the key points within, and summarize them into a coherent and fluent text while paraphrasing the document. It is sampled from IndoNLI for Indonesian, IndicXNLI for Tamil, and XNLI for Thai and Vietnamese.
Supported Tasks and Leaderboards
SEA Abstractive Summarization is designed for evaluating chat or instruction-tuned large language models (LLMs). It… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/NLR-NLI.FOL-nli
Dataset Card for "FOL-nli"
https://github.com/sileod/unigram/
https://arxiv.org/abs/2406.11035
Citation:
@article{sileo2024scaling,
title={Scaling Synthetic Logical Reasoning Datasets with Context-Sensitive Declarative Grammars},
author={Sileo, Damien},
journal={arXiv preprint arXiv:2406.11035},
year={2024}
}
math_benchmark_test_saturation
LLM Leaderboard Data for Hendrycks MATH Dataset (2022–2024)
This dataset aggregates yearly performance (2022–2024) of large language models (LLMs) on the Hendrycks MATH benchmark. It is specifically compiled to explore performance evolution, benchmark saturation, parameter scaling trends, and evaluation metrics of foundation models solving complex math word problems.
Original source data: Math Word Problem Solving on MATH (Papers with Code)
About Hendrycks' MATH… See the full description on the dataset page: https://huggingface.co/datasets/nlile/math_benchmark_test_saturation.nli_it_collection
Dataset Card for Natural Language Inference Instruction Tuning Collection
This dataset is a collection of various NLI datasets in Czech and English, transformed into an instruction tuning format based on the FLAN approach.
Dataset Details
Dataset Description
This dataset is a collection of English and Czech NLI datasets. Its primary purpose is instruction tuning (supervised fine tuning) of decoder LLMs. The used datasets were converted using a FLAN-like… See the full description on the dataset page: https://huggingface.co/datasets/ctu-aic/nli_it_collection.task936_defeasible_nli_snli_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task936_defeasible_nli_snli_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task936_defeasible_nli_snli_classification.DIWALI
DIWALI - Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context
Paper | Code | Project page
We present a novel Culture Specific Items (CSIs) dataset for Indian culture covering 17 facets. Please refer to our project pagefor quick details.
Facets considered: food, dance, festivals, names, jewellery, places, traditions, languages, clothing, games, rituals, architectures, drinks, arts… See the full description on the dataset page: https://huggingface.co/datasets/nlip/DIWALI.peerreview-bench
PeerReview Bench
Expert-annotated review items from scientific papers, organized for three
complementary evaluation tasks. All data in this dataset is intended
for evaluation, not training. All configs reference a shared, deduplicated
file store (submitted_papers) via SHA256 content hashes.
Every config exposes a single eval split.
Configs
reviewer
For evaluating AI reviewers (models that generate reviews from a paper).
One row per paper.
Minimal fields:… See the full description on the dataset page: https://huggingface.co/datasets/nlile/peerreview-bench.rewrite-questions-nonsensical-biology
nonsensical_biology.csv - Question Rewriting Dataset
This dataset contains question rewriting outputs from the file nonsensical_biology.csv.
Dataset Structure
The dataset contains the following columns:
custom_id: Unique identifier for each question
style: Rewriting style applied (e.g., "gibberish")
index: Numerical index
original: Original question text
rewritten: Rewritten version of the question
options: Multiple choice options (list format)
correct: Index of the… See the full description on the dataset page: https://huggingface.co/datasets/NLie2/rewrite-questions-nonsensical-biology.rewrite-questions-real-words-sciency
real_words_sciency.csv - Question Rewriting Dataset
This dataset contains question rewriting outputs from the file real_words_sciency.csv.
Dataset Structure
The dataset contains the following columns:
custom_id: Unique identifier for each question
style: Rewriting style applied (e.g., "gibberish")
index: Numerical index
original: Original question text
rewritten: Rewritten version of the question
options: Multiple choice options (list format)
correct: Index of the… See the full description on the dataset page: https://huggingface.co/datasets/NLie2/rewrite-questions-real-words-sciency.task937_defeasible_nli_social_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task937_defeasible_nli_social_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task937_defeasible_nli_social_classification.rewrite-questions-gibberish
gibberish.csv - Question Rewriting Dataset
This dataset contains question rewriting outputs from the file gibberish.csv.
Dataset Structure
The dataset contains the following columns:
custom_id: Unique identifier for each question
style: Rewriting style applied (e.g., "gibberish")
index: Numerical index
original: Original question text
rewritten: Rewritten version of the question
options: Multiple choice options (list format)
correct: Index of the correct answer… See the full description on the dataset page: https://huggingface.co/datasets/NLie2/rewrite-questions-gibberish.all_nli_marathi
All Nli Marathi Dataset: High-Quality Marathi NLP Corpus
📌 Overview
The All Nli Marathi dataset is a meticulously curated collection of 570810 rows of Marathi text, ensuring linguistic accuracy and natural flow. Every sentence has been verified by native Marathi speakers to maintain contextual integrity and correctness.
This dataset is designed for semantic search, text classification, and various NLP tasks, making it a valuable resource for machine learning models… See the full description on the dataset page: https://huggingface.co/datasets/Singhchandann/all_nli_marathi.task935_defeasible_nli_atomic_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task935_defeasible_nli_atomic_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task935_defeasible_nli_atomic_classification.all-nli-pair-score_marathi
All-Nli-Pair-Score Marathi Dataset: High-Quality Marathi NLP Corpus
📌 Overview
The All-Nli-Pair-Score Marathi dataset is a meticulously curated collection of 981336 rows of Marathi text, ensuring linguistic accuracy and natural flow. Every sentence has been verified by native Marathi speakers to maintain contextual integrity and correctness.
This dataset is designed for semantic search, text classification, and various NLP tasks, making it a valuable resource for machine… See the full description on the dataset page: https://huggingface.co/datasets/Singhchandann/all-nli-pair-score_marathi.nli-for-simcse_marathi
Nli-For-Simcse Marathi Dataset: High-Quality Marathi NLP Corpus
📌 Overview
The Nli-For-Simcse Marathi dataset is a meticulously curated collection of 274951 rows of Marathi text, ensuring linguistic accuracy and natural flow. Every sentence has been verified by native Marathi speakers to maintain contextual integrity and correctness.
This dataset is designed for semantic search, text classification, and various NLP tasks, making it a valuable resource for machine… See the full description on the dataset page: https://huggingface.co/datasets/Singhchandann/nli-for-simcse_marathi.nli_dataset
NLI Task Specification Dataset (MASL)
Авторы: Рудаков И. С., Понимаш З. А
Описание датасета
Синтетический датасет для задачи преобразования команд на естественном языке в структурированное описание задач с использованием формата MASL (Multi-agent system language).
Датасет содержит 9 999 примеров пар:
Входные данные: текстовая команда пользователя на русском языке
Выходные данные: JSON структура с входными и выходными коннекторами
Назначение
Датасет… See the full description on the dataset page: https://huggingface.co/datasets/Ponimash/nli_dataset.