Remove mentions of RAG from the docs (#7376)

* Remove mentions of  RAG from the docs

* Deactivate check
This commit is contained in:
Sylvain Gugger
2020-09-24 17:07:14 -04:00
committed by GitHub
parent eadd870b2f
commit a8e7982f84
4 changed files with 3 additions and 115 deletions

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@@ -672,27 +672,6 @@ DPR consists in three models:
DPR's pipeline (not implemented yet) uses a retrieval step to find the top k contexts given a certain question, and then it calls the reader with the question and the retrieved documents to get the answer.
RAG
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.. raw:: html
<a href="https://huggingface.co/models?filter=rag">
<img alt="Models" src="https://img.shields.io/badge/All_model_pages-rag-blueviolet">
</a>
<a href="model_doc/rag.html">
<img alt="Doc" src="https://img.shields.io/badge/Model_documentation-rag-blueviolet">
</a>
`Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks <https://arxiv.org/abs/2005.11401>`_,
Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela
Retrieval-augmented generation ("RAG") models combine the powers of pretrained dense retrieval (DPR) and Seq2Seq models.
RAG models retrieve docs, pass them to a seq2seq model, then marginalize to generate outputs.
The retriever and seq2seq modules are initialized from pretrained models, and fine-tuned jointly, allowing both retrieval and generation to adapt to downstream tasks.
The two models RAG-Token and RAG-Sequence are available for generation.
More technical aspects
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