Task Adapters

Drop

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. . DROP is a crowdsourced, adversarially-created, 96k-question benchmark, in which a system must resolve references in a question, perhaps to multiple input positions, and perform discrete operations over them (such as addition, counting, or sorting). These operations require a much more comprehensive understanding of the content of paragraphs than what was necessary for prior datasets.

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AdapterHub/bert-base-uncased-pf-drop bert-base-uncased

huggingface.co Head:

# Adapter `AdapterHub/bert-base-uncased-pf-drop` for bert-base-uncased An [adapter](https://adapterhub.ml) for the `bert-base-uncased` model that was trained on the...

AdapterHub/roberta-base-pf-drop roberta-base

huggingface.co Head:

# Adapter `AdapterHub/roberta-base-pf-drop` for roberta-base An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [drop](https://huggingface.co/datasets/drop/)...