Question generation
tifa-benchmark_-_llama2_tifa_question_generation-gguft5-base-finetuned-question-generation-apLucas-Hyun-Lee_-_gemma-2b-it-Question-generation-en-sft-qlora-gguft5-large-generation-squad-QuestionAnswert5-base-e2e-question-generationLucas-Hyun-Lee-gemma-2b-it-Question-generation-en-sft-qlora-GGUFniryuu-tinyllama-task003_mctaco_question_generation_event_duration-v1-GGUFT5-Base-finetuned-for-Question-Generation
task821_protoqa_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task821_protoqa_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/task821_protoqa_question_generation.task670_ambigqa_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task670_ambigqa_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/task670_ambigqa_question_generation.task246_dream_question_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task246_dream_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/task246_dream_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.task1325_qa_zre_question_generation_on_subject_relation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1325_qa_zre_question_generation_on_subject_relation
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/task1325_qa_zre_question_generation_on_subject_relation.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.