commonsense
Commonsense-QA-Mistral-7B-Mistral-7B-Instruct-v0.2-slerp-GGUFautoprogrammer_-_Llama-3.2-1B-Instruct-commonsenseqa-zh-slerp-ggufautoprogrammer_-_Llama-3.2-1B-Instruct-commonsense_qa-zh-linear-ggufCommonsense-QA-Mistral-7B-i1-GGUFautoprogrammer_-_Llama-3.2-1B-Instruct-commonsense_qa-medmcqa-block-ggufPiSSA-llama-7b-commonsense-148k-i1-GGUFPiSSA-Llama-3-8b-commonsense-148k-GGUFank028_-_Llama-3.2-1B-Instruct-commonsense_qa-gguf
commonsense_qa
Dataset Card for "commonsense_qa"
Dataset Summary
CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge
to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.
The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation
split, and "Question token split", see paper for details.… See the full description on the dataset page: https://huggingface.co/datasets/tau/commonsense_qa.commonsense-qaphysical-commonsensecommonsense_qa_2.0https://github.com/allenai/csqa2
@article{talmor2022commonsenseqa,
title={CommonsenseQA 2.0: Exposing the limits of AI through gamification},
author={Talmor, Alon and Yoran, Ori and Bras, Ronan Le and Bhagavatula, Chandra and Goldberg, Yoav and Choi, Yejin and Berant, Jonathan},
journal={arXiv preprint arXiv:2201.05320},
year={2022}
}
DemoFeedbackcommonsense_170khttps://github.com/AGI-Edgerunners/LLM-Adapters/blob/main/ft-training_set/commonsense_170k.json