AdapterHub
  •   Explore
  •   Upload
  •   Docs
  •   Blog
  •  
  •  
  1. Explore
  2. Task

Task Adapters

Pre-trained model:

All architectures
All architectures
bert bart xlm-roberta distilbert gpt2 roberta mbart

Com Qa

ComQA is a dataset of 11,214 questions, which were collected from WikiAnswers, a community question answering website. By collecting questions from such a site we ensure that the information needs are ones of interest to actual users. Moreover, questions posed there are often cannot be answered by commercial search engines or QA technology, making them more interesting for driving future research compared to those collected from an engine's query log. The dataset contains questions with various challenging phenomena such as the need for temporal reasoning, comparison (e.g., comparatives, superlatives, ordinals), compositionality (multiple, possibly nested, subquestions with multiple entities), and unanswerable questions (e.g., Who was the first human being on Mars?). Through a large crowdsourcing effort, questions in ComQA are grouped into 4,834 paraphrase clusters that express the same information need. Each cluster is annotated with its answer(s). ComQA answers come in the form of Wikipedia entities wherever possible. Wherever the answers are temporal or measurable quantities, TIMEX3 and the International System of Units (SI) are used for normalization.
🤗  huggingface.co
AdapterHub/bert-base-uncased-pf-comqa bert-base-uncased
huggingface.co Head: 

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

AdapterHub/roberta-base-pf-comqa roberta-base
huggingface.co Head: 

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

Paper | Imprint & Privacy

Brought to you with ❤️  by authors from: