multiple-label
aift-model-review-multiple-label-classificationfinetuned-Accident-MultipleLabels-Video-subset-v2finetuned-Accident-MultipleLabels-Video-subset-v2-checkpointingfinetuned-Accident-MultipleLabels-Video-subsetfinetuned-Accident-MultipleLabels-Video-subset-v2-newfinetuned-Accident-MultipleLabels-Others-v2finetuned-Accident-MultipleLabels-Video-subset-v2-new1insurance_multiple_label_my83
labeled-multiple-choice-explained-mistral-reasoninglabeled-multiple-choice-explained-falcon-reasoninglabeled-multiple-choice-explainedThis dataset is based on under-tree/labeled-multiple-choice but using GPT-3.5-turbo to generate explanations for each answer option.
This was a very basic attempt to follow the Orca paper approach of a 'teacher' model to provide more context to some trivia questions.
Questions were deduplicated based on the question text.
I used the python library guidance to help generate the prompts. Below is the prompt template I used.
{{#role 'system'~}}
You are an AI assistant that helps people find… See the full description on the dataset page: https://huggingface.co/datasets/layoric/labeled-multiple-choice-explained.labeled-multiple-choice-explained-falcon-tokenizedlabeled-multiple-choice-explainedlabeled-multiple-choice
Dataset Card for "labeled-multiple-choice"
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