datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
InternSpatialqasper-yesnosciriff-yesnoOCR-Data
OCR Text Detection and Recognition Dataset
Dataset Description
A large-scale, multi-source OCR dataset aggregating 14 public benchmarks for text detection and recognition in both scene images and handwritten documents. Each image is paired with:
Transcribed text for each text region
Bounding boxes (axis-aligned rectangles) for each text region
Polygon coordinates (precise boundary points) for each text region
The dataset is stored in HuggingFace Parquet format with… See the full description on the dataset page: https://huggingface.co/datasets/Yesianrohn/OCR-Data.Health_Benchmarks
LLM Health Benchmarks Dataset by Yesil Science
The LLM Health Benchmarks Dataset is a specialized resource for evaluating large language models (LLMs) in different medical specialties. It provides structured question-answer pairs designed to test the performance of AI models in understanding and generating domain-specific knowledge.
Primary Purpose
This dataset is built to:
Benchmark LLMs in medical specialties and subfields.
Assess the accuracy and contextual… See the full description on the dataset page: https://huggingface.co/datasets/yesilhealth/Health_Benchmarks.bioasq_7b_yesno100k_movie_reviews_from_kz
100,000+ Movie Reviews from Kazakhstan: Russian, Kazakh, and Code-Switched Texts
Dataset Summary
This repository provides a publicly available corpus of 100,502 movie reviews collected from kino.kz, spanning 2001–2025 and covering 4,943 unique movie titles. The dataset is multilingual and reflects a Kazakhstan-specific online setting where reviews are predominantly written in Russian, with smaller subsets in Kazakh and Kazakh–Russian code-switched text.
Reviews are… See the full description on the dataset page: https://huggingface.co/datasets/yeshpanovrustem/100k_movie_reviews_from_kz.bioasq_yesno_trainv0_n1464_test100msmarco-yesnobioasq-yesno-cleankaznerd
A Named Entity Recognition Dataset for Kazakh
This is a modified version of the dataset provided in the LREC 2022 paper KazNERD: Kazakh Named Entity Recognition Dataset.
The original repository for the paper can be found at https://github.com/IS2AI/KazNERD.
Tokens denoting speech disfluencies and hesitations (parenthesised) and background noise [bracketed] were removed.
A total of 2,027 duplicate sentences were removed.
Statistics for training (Train), validation (Valid)… See the full description on the dataset page: https://huggingface.co/datasets/yeshpanovrustem/kaznerd.MLT2019task380_boolq_yes_no_question
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task380_boolq_yes_no_question
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 Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task380_boolq_yes_no_question.reward-bench-Qwen2.5-3B-yes-noreward-bench-chatgpt-4o-latest-yes-noreward-bench-Phi-3-mini-128k-instruct-yes-notask362_spolin_yesand_prompt_response_sub_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task362_spolin_yesand_prompt_response_sub_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… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task362_spolin_yesand_prompt_response_sub_classification.hotpot_qa
Dataset Card for "hotpot_qa"
Dataset Summary
HotpotQA is a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowingQA systems to reason… See the full description on the dataset page: https://huggingface.co/datasets/Yeshenyue/hotpot_qa.reward-bench-Qwen2.5-7B-Instruct-yes-noreward-bench-Llama-3.2-1B-yes-noreward-bench-Llama-3.2-3B-yes-noreward-bench-Qwen2.5-0.5B-yes-noyesreward-bench-Llama-2-13b-chat-hf-yes-noreward-bench-Qwen2.5-7B-yes-noreward-bench-Qwen2.5-0.5B-Instruct-yes-noreward-bench-gemma-2-2b-it-yes-noreward-bench-gpt2-yes-noreward-bench-gpt-4o-mini-yes-noreward-bench-pythia-6.9b-yes-no