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README.md
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license: apache-2.0
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---
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---
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tags:
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- Generative QA
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- LFQA
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- ELI5
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- facebook/bart-large
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license: apache-2.0
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---
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# Model description
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A Fusion in Decoder(FiD) model based on BART for the [KILT-ELI5](https://github.com/facebookresearch/KILT) task.
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The FiD model was in introduced in the paper 'Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering'.
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The model has been initialized with [facebook/bart-large](https://huggingface.co/facebook/bart-large).
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The model was trained with the KILT-ELI5 questions and supporting passages obtained from a ColBERT index of the 2019/08/01 Wikipedia dump.
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## Intended uses & limitations
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You can use the raw model for the generative question answering task. Biases associated with the pre-existing language model, facebook/bart-large, that we used may be present in our fine-tuned model.
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## Usage
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You can use this model directly with the [PrimeQA](https://github.com/primeqa/primeqa)'s [Generative FiD Reader](https://github.com/primeqa/primeqa/tree/primeqa-fid/primeqa/pipelines#readme).
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### BibTeX entry and citation info
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```bibtex
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@inproceedings{Izacard2021LeveragingPR,
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title={Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering},
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author={Gautier Izacard and Edouard Grave},
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booktitle={EACL},
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year={2021}
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}
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```
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```bibtex
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@inproceedings{petroni-etal-2021-kilt,
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title = "{KILT}: a Benchmark for Knowledge Intensive Language Tasks",
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author = {Petroni, Fabio and Piktus, Aleksandra and
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Fan, Angela and Lewis, Patrick and
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Yazdani, Majid and De Cao, Nicola and
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Thorne, James and Jernite, Yacine and
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Karpukhin, Vladimir and Maillard, Jean and
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Plachouras, Vassilis and Rockt{\"a}schel, Tim and
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Riedel, Sebastian},
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booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association
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for Computational Linguistics: Human Language Technologies",
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year = "2021",
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}
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```
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