datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NLU-Question-Answering
SEA Question Answering
SEA Question Answering evaluates a model's ability to predict a contiguous span of characters that answers the question about a given passage. It is sampled from TyDi QA-GoldP for Indonesian, IndicQA for Tamil, and XQuaD for Thai and Vietnamese.
Supported Tasks and Leaderboards
SEA Question Answering is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.… See the full description on the dataset page: https://huggingface.co/datasets/aisingapore/NLU-Question-Answering.task290_tellmewhy_question_answerability
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task290_tellmewhy_question_answerability
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/task290_tellmewhy_question_answerability.task861_asdiv_addsub_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task861_asdiv_addsub_question_answering
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/task861_asdiv_addsub_question_answering.task865_mawps_addsub_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task865_mawps_addsub_question_answering
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/task865_mawps_addsub_question_answering.task864_asdiv_singleop_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task864_asdiv_singleop_question_answering
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/task864_asdiv_singleop_question_answering.task1594_yahoo_answers_topics_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1594_yahoo_answers_topics_question_generation
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… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1594_yahoo_answers_topics_question_generation.task752_svamp_multiplication_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task752_svamp_multiplication_question_answering
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+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task752_svamp_multiplication_question_answering.task1326_qa_zre_question_generation_from_answer
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1326_qa_zre_question_generation_from_answer
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+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1326_qa_zre_question_generation_from_answer.task867_mawps_multiop_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task867_mawps_multiop_question_answering
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/task867_mawps_multiop_question_answering.task1731_quartz_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1731_quartz_question_answering
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/task1731_quartz_question_answering.task144_subjqa_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task144_subjqa_question_answering
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/task144_subjqa_question_answering.task754_svamp_common-division_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task754_svamp_common-division_question_answering
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+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task754_svamp_common-division_question_answering.task753_svamp_addition_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task753_svamp_addition_question_answering
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/task753_svamp_addition_question_answering.task751_svamp_subtraction_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task751_svamp_subtraction_question_answering
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/task751_svamp_subtraction_question_answering.task1286_openbookqa_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1286_openbookqa_question_answering
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/task1286_openbookqa_question_answering.task178_quartz_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task178_quartz_question_answering
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/task178_quartz_question_answering.task868_mawps_singleop_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task868_mawps_singleop_question_answering
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/task868_mawps_singleop_question_answering.civil-human-rights-question-answering
Dataset Card for 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/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/civil-human-rights-question-answering.question-answer-Subject-Finance-Instructobekt-question-answer-reasoning-micro-v0.1
Obekt Micro Reasoning Dataset (v0.1)
Dataset Description
This is a "micro" dataset containing questions, answers, and reasoning traces. It is generated using the Xiaomi MiMo V2 Flash LLM and is intended for experimental purposes, quick prototyping, and fine-tuning trials where reasoning capability is a focus.
Source Model: xiaomi/mimo-v2-flash
Contains
obekt-question-answer-reasoning-micro-v0.1.csv: The main data file.
Columns:
question: The input query.… See the full description on the dataset page: https://huggingface.co/datasets/obekt/obekt-question-answer-reasoning-micro-v0.1.newsquadfr_fr_prompt_question_generation_with_answer
newsquadfr_fr_prompt_question_generation_with_answer
Summary
newsquadfr_fr_prompt_question_generation_with_answer is a subset of the Dataset of French Prompts (DFP).It contains 92,620 rows that can be used for a question-generation (with answer) task.The original data (without prompts) comes from the dataset newsquadfr and was augmented by questions in SQUAD 2.0 format in the FrenchQA dataset.
A list of prompts (see below) was then applied in order to build the input and… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/newsquadfr_fr_prompt_question_generation_with_answer.piaf_fr_prompt_context_generation_with_answer_and_question
piaf_fr_prompt_context_generation_with_answer_and_question
Summary
piaf_fr_prompt_context_generation_with_answer_and_question is a subset of the Dataset of French Prompts (DFP).It contains 442,752 rows that can be used for a context-generation (with answer and question) task.The original data (without prompts) comes from the dataset PIAF and was augmented by questions in SQUAD 2.0 format in the FrenchQA dataset.
A list of prompts (see below) was then applied in order to… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/piaf_fr_prompt_context_generation_with_answer_and_question.obekt-question-answer-reasoning-nano-v0.1
Obekt Nano Reasoning Dataset (v0.1)
Dataset Description
This is a small "nano" dataset containing questions, answers, and reasoning traces. It is generated using the Xiaomi MiMo V2 Flash LLM and is intended for experimental purposes, quick prototyping, and fine-tuning trials where reasoning capability is a focus.
Source Model: xiaomi/mimo-v2-flash
Contains
obekt-question-answer-reasoning-nano-v0.1.csv: The main data file.
Columns:
question: The input query.… See the full description on the dataset page: https://huggingface.co/datasets/obekt/obekt-question-answer-reasoning-nano-v0.1.piaf_fr_prompt_question_generation_with_answer
piaf_fr_prompt_question_generation_with_answer
Summary
piaf_fr_prompt_question_generation_with_answer is a subset of the Dataset of French Prompts (DFP).It contains 387,408 rows that can be used for a question-generation (with answer) task.The original data (without prompts) comes from the dataset PIAF and was augmented by questions in SQUAD 2.0 format in the FrenchQA dataset.
A list of prompts (see below) was then applied in order to build the input and target columns… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/piaf_fr_prompt_question_generation_with_answer.squad_v2_french_translated_fr_prompt_context_generation_with_answer_and_question
squad_v2_french_translated_fr_prompt_context_generation_with_answer_and_question
Summary
squad_v2_french_translated_fr_prompt_context_generation_with_answer_and_question is a subset of the Dataset of French Prompts (DFP).It contains 1,271,928 rows that can be used for a context-generation (with answer and question) task.The original data (without prompts) comes from the dataset pragnakalp/squad_v2_french_translated and was augmented by questions in SQUAD 2.0 format in the… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/squad_v2_french_translated_fr_prompt_context_generation_with_answer_and_question.task1640_aqa1.0_answerable_unanswerable_question_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1640_aqa1.0_answerable_unanswerable_question_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… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1640_aqa1.0_answerable_unanswerable_question_classification.newsquadfr_fr_prompt_question_generation_with_answer_and_context
newsquadfr_fr_prompt_question_generation_with_answer_and_context
Summary
newsquadfr_fr_prompt_question_generation_with_answer_and_context is a subset of the Dataset of French Prompts (DFP).It contains 88,410 rows that can be used for a question generation (with answer and context) task.The original data (without prompts) comes from the dataset newsquadfr and was augmented by questions in SQUAD 2.0 format in the FrenchQA dataset.
A list of prompts (see below) was then… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/newsquadfr_fr_prompt_question_generation_with_answer_and_context.newsquadfr_fr_prompt_context_generation_with_answer_and_question
newsquadfr_fr_prompt_context_generation_with_answer_and_question
Summary
newsquadfr_fr_prompt_context_generation_with_answer_and_question is a subset of the Dataset of French Prompts (DFP).It contains 101,040 rows that can be used for a context-generation (with answer)task.The original data (without prompts) comes from the dataset newsquadfr and was augmented by questions in SQUAD 2.0 format in the FrenchQA dataset.
A list of prompts (see below) was then applied in order… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/newsquadfr_fr_prompt_context_generation_with_answer_and_question.task866_mawps_multidiv_question_answering
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task866_mawps_multidiv_question_answering
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/task866_mawps_multidiv_question_answering.squad_v2_french_translated_fr_prompt_question_generation_with_answer_and_context
squad_v2_french_translated_fr_prompt_question_generation_with_answer_and_context
Summary
squad_v2_french_translated_fr_prompt_question_generation_with_answer_and_context is a subset of the Dataset of French Prompts (DFP).It contains 1,112,937 rows that can be used for a question-generation (with answer and context) task.The original data (without prompts) comes from the dataset pragnakalp/squad_v2_french_translated and was augmented by questions in SQUAD 2.0 format in the… See the full description on the dataset page: https://huggingface.co/datasets/CATIE-AQ/squad_v2_french_translated_fr_prompt_question_generation_with_answer_and_context.