question generation
tifa-benchmark_-_llama2_tifa_question_generation-gguft5-base-finetuned-question-generation-apLucas-Hyun-Lee_-_gemma-2b-it-Question-generation-en-sft-qlora-ggufLucas-Hyun-Lee-gemma-2b-it-Question-generation-en-sft-qlora-GGUFt5-base-e2e-question-generationt5-large-generation-squad-QuestionAnswerniryuu-tinyllama-task003_mctaco_question_generation_event_duration-v1-GGUFllama2_tifa_question_generation
squad-v1.1-t5-question-generation
Dataset Card for "squad-v1.1-t5-question-generation"
Dataset Summary
This is a modified Stanford Question Answering Dataset (SQuAD) to suit question generation with All Questions in One Line (AQOL) just like in Transformer-based End-to-End Question Generation
specifically for the T5 family of models. The prefix is generate questions: so that the task can be unique to a trained model.
Check out the generation notebook here.
Supported Tasks and Leaderboards… See the full description on the dataset page: https://huggingface.co/datasets/derek-thomas/squad-v1.1-t5-question-generation.task442_com_qa_paraphrase_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task442_com_qa_paraphrase_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 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task442_com_qa_paraphrase_question_generation.task1657_gooaq_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1657_gooaq_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 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1657_gooaq_question_generation.Question-Answering-Generation-Choices
The dataset is a merged compilation of QuAIL, RACE, and Cosmos QA datasets,
having undergone preprocessing.
Question-GenerationThis is the question generation datasets collected by TextBox, including:
SQuAD (squadqg)
CoQA (coqaqg)
NewsQA (newsqa)
HotpotQA (hotpotqa)
MS MARCO (marco)
MSQG (msqg)
NarrativeQA (nqa)
QuAC (quac).
The detail and leaderboard of each dataset can be found in TextBox page.
task074_squad1.1_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task074_squad1.1_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 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task074_squad1.1_question_generation.