README.md

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title: README
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<h3 align="center">
    <img width="350" alt="primeqa" src="docs/_static/img/PrimeQA.png">
    <p>The prime repository for state-of-the-art Multilingual and Multimedia Question Answering research and development.</p>
</h3>

This is the main location for fine-tuned models from the PrimeQA repository. PrimeQA is a public open source repository that enables researchers and developers to train state-of-the-art models for question answering (QA). By using PrimeQA, a researcher can replicate the experiments outlined in a paper published in the latest NLP conference while also enjoying the capability to download pre-trained models (from an online repository) and run them on their own custom data. PrimeQA is built on top of the [Transformers](https://github.com/huggingface/transformers) toolkit and uses [datasets](https://huggingface.co/datasets/viewer/) and [models](https://huggingface.co/PrimeQA) that are directly downloadable.


The models within PrimeQA supports End-to-end Question Answering. PrimeQA answers questions via 
- [Information Retrieval](https://github.com/primeqa/primeqa/tree/main/primeqa/ir): Retrieving documents and passages using both traditional (e.g. BM25) and neural (e.g. ColBERT) models
- [Multilingual Machine Reading Comprehension](https://huggingface.co/ibm/tydiqa-primary-task-xlm-roberta-large): Extract and/ or generate answers given the source document or passage.
- [Multilingual Question Generation](https://huggingface.co/PrimeQA/mt5-base-tydi-question-generator): Supports generation of questions for effective domain adaptation over [tables](https://huggingface.co/PrimeQA/t5-base-table-question-generator) and [multilingual text](https://huggingface.co/PrimeQA/mt5-base-tydi-question-generator).