datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bayan-simplification-corpus
Synthetic simplification data card — v1
Versions. main and the v1 tag hold v1 (Gemma 4 31B generator, Qwen3.8 27B judge). The previous
DeepSeek release is kept at the v0 tag: load_dataset("Congi-libya/bayan-simplification-corpus", revision="v0").
A full v0 vs v1 comparison is in Cogni-Libya/Bayan#45.
Paths under scripts/ and docs/ refer to the Bayan repository;
paths under data/processed/ are the project's working files and are not part of this dataset.
Version 1 of… See the full description on the dataset page: https://huggingface.co/datasets/Congi-libya/bayan-simplification-corpus.age-specific-text-simplification
Age-Specific Text Simplification Dataset
Dataset Description
This dataset contains complex texts simplified into age-appropriate versions for children aged 3, 4, and 5 years old. Each original text has been professionally adapted to match the cognitive development, vocabulary, and comprehension abilities of each specific age group.
Dataset Summary
Total Examples: 17,177
Training Split: 15,459 examples
Validation Split: 1,718 examples
Languages:… See the full description on the dataset page: https://huggingface.co/datasets/hasankursun/age-specific-text-simplification.task934_turk_simplification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task934_turk_simplification
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/task934_turk_simplification.Leesplank_NL_wikipedia_simplificationsThe set contains 2.87M pragraphs of prompt/result combinations, where the prompt is a paragraph from Dutch Wikipedia and the result is a simplified text, which could include more than one paragraph.
This dataset was created by UWV, as a part of project "Leesplank", an effort to generate datasets that are ethically and legally sound.
The basis of this dataset was the wikipedia extract as a part of Gigacorpus (http://gigacorpus.nl/). The lines were fed one by one into GPT 4 1106 preview, where… See the full description on the dataset page: https://huggingface.co/datasets/UWV/Leesplank_NL_wikipedia_simplifications.medical-reports-simplification-dataset
🏥 Medical Reports Simplification Dataset
📋 Description
Dataset créé avec Gemini 2.5 Pro (Preview) pour entraîner des modèles à simplifier les rapports médicaux complexes en explications compréhensibles pour les patients.
🎯 Objectif : Démocratiser l'accès à l'information médicale en rendant les rapports techniques accessibles au grand public.
🔧 Génération du Dataset
Génération : Gemini 2.5 Pro (Preview)
Validation : Contrôle qualité automatisé… See the full description on the dataset page: https://huggingface.co/datasets/Sadou/medical-reports-simplification-dataset.task111_asset_sentence_simplification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task111_asset_sentence_simplification
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/task111_asset_sentence_simplification.nemotron-cc-atomic-simplification-gemma4-31b
nemotron-cc atomic-statement simplification (Gemma 4 31B-it)
2,000,000 records: source text from
nvidia/nemotron-cc-v2.1 (High-Quality-Synthetic
split) rewritten by google/gemma-4-31B-it into a sequence of atomic, Subject-Verb-Object
statements.
Generated with vLLM 0.22.1 in-process batch inference (see src/generate/run.py in the
producing repo), TP=4, max_model_len=16384, max_tokens=8192, prompts filtered to
<=8192 templated tokens.
Fields
id: original… See the full description on the dataset page: https://huggingface.co/datasets/rpisano/nemotron-cc-atomic-simplification-gemma4-31b.