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Tel Aviv University

tau

Models in Library1
Datasets in Library1
Models on Hugging Face89
Followers88

Models

Model · Question answering

splinter-base

Tel Aviv University

Splinter-base is the pretrained model discussed in the paper Few-Shot Question Answering by Pretraining Span Selection (at ACL 2021). Its original repository can be found here. The model is case-sensitive. Note: This model doesn't contain the pretrained weights for the QASS layer (see paper for details), and therefore the QASS layer is randomly initialized upon loading it. For the model with those weights, see tau/splinter-base-qass. Splinter is a model that is pretrained in a self-supervised fashion for few-shot question answering. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an…

Open weights apache-2.0 512 tokens transformers

Datasets

Dataset · Question answering

commonsense_qa

Tel Aviv University

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. The dataset is in English (en). An example of 'train' looks as follows: The data fields are the same among all splits. - id (str): Unique ID. - question: a string feature. - questionconcept (str): ConceptNet concept associated to the question. - choices: a dictionary feature…

Publicly accessible mit 1K<n<10K