datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
qa_harvesting_from_wikipedia_pseudo
Dataset Card for "lmqg/qa_harvesting_from_wikipedia_pseudo"
Dataset Summary
This is a synthetic QA dataset generated with fine-tuned QG models over lmqg/qa_harvesting_from_wikipedia, 1 million paragraph and answer pairs collected in Du and Cardie, 2018, made for question-answering based evaluation (QAE) for question generation model proposed by Zhang and Bansal, 2019.
The train split is the synthetic data and the validation split is the original validation set of SQuAD… See the full description on the dataset page: https://huggingface.co/datasets/lmqg/qa_harvesting_from_wikipedia_pseudo.rag-human-rights-from-files
Dataset Card for my-distiset-rag-files
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/sdiazlor/my-distiset-rag-files/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/sdiazlor/rag-human-rights-from-files.ChatGPT-Jailbreak-Prompts-rubend18
Dataset Card for Dataset Name
Name
ChatGPT Jailbreak Prompts
Dataset Summary
ChatGPT Jailbreak Prompts is a complete collection of jailbreak related prompts for ChatGPT. This dataset is intended to provide a valuable resource for understanding and generating text in the context of jailbreaking in ChatGPT.
Languages
[English]
qa_harvesting_from_wikipediaQA pairs generated in https://aclanthology.org/P18-1177/DeepSeek-R1-Distill-Qwen-32B-LeaPPaper: Learning from Peers in Reasoning Models
Project Page: https://learning-from-peers.github.io/
Code: https://github.com/tongxuluo/LeaP
rag-human-rights-from-prompt
Dataset Card for datset-rag-prompt
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/sdiazlor/datset-rag-prompt/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/sdiazlor/rag-human-rights-from-prompt.QA_from_CoVLA
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 Needed]
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… See the full description on the dataset page: https://huggingface.co/datasets/Egikk/QA_from_CoVLA.From_atomic_to_compositeThis repo contains the raw data for the paper From Atomic to Composite: Reinforcement Learning Enables Generalization in Complementary Reasoning with human biographies from a synthetic knowledge graph.
The code to generate these data is available at https://github.com/sitaocheng/from_atomic_to_composite.
The data can be directly adapted to frameworks like LLamafactory or VeRL.
We opensource the training and testing data for parametric, contextual and complementary reasoning, respectively.… See the full description on the dataset page: https://huggingface.co/datasets/sitao/From_atomic_to_composite.great-works-from-africa-and-the-pacific-bernard-de-grunne-new-york-2008
large-chunk-ocr-data
Dataset created with PDF2Dataset -- OCR + structure-aware chunking pipeline.
Dataset Summary
Metric
Value
Total chunks
31
Avg chars/chunk
731
Avg images/chunk
1.58
Source files
1
Duplicates removed
0
Quality filtered
1
Schema
Column
Type
Description
chunk_id
string
Unique identifier: filename_chunk_N
text
string
Raw markdown chunk with image refs
text_clean
string
Cleaned text without… See the full description on the dataset page: https://huggingface.co/datasets/Svngoku/great-works-from-africa-and-the-pacific-bernard-de-grunne-new-york-2008.qa-from-abstract-graphenepcos-management-patient-qa-from-eshre-guideline
Dataset Card for pcos-management-patient-qa-from-eshre-guideline
Dataset Details
Dataset Description
pcos-management-patient-qa-from-eshre-guideline is a clinically grounded conversational dataset designed to support training and evaluation of chat-based AI models for patient education in Polycystic Ovary Syndrome (PCOS).
The dataset contains structured user–assistant conversations derived from evidence-based recommendations in the International Evidence-based… See the full description on the dataset page: https://huggingface.co/datasets/Khyatimirani/pcos-management-patient-qa-from-eshre-guideline.prompts-classification-pfggame_data
game_data
Multi-task reasoning dataset. Each task type is a separate config with train/test/dev splits.
Usage
from datasets import load_dataset
# Load a specific task and split
ds = load_dataset("CL-From-Nothing/game_data", "futoshiki", split="train")
ds = load_dataset("CL-From-Nothing/game_data", "minesweeper", split="test")
Available Tasks
futoshiki, kukurasu, minesweeper, sudoku
Available Splits
train, test, dev