How to build a Q&A Reader Model in Python (Open-domain QA)
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Open-domain question-answering (ODQA) is a wildly popular *pipeline* of databases and language models that allow us to ask a machine human-like questions and return comprehensible and even intelligent answers.

Despite the outward guise of simplicity, ODQA requires a reasonably advanced set of components placed together to enable the *extractive* Q&A functionality.

We call this *extractive* Q&A because the models are not generating an answer. Instead, the answer already exists but is hidden somewhere within potentially thousands, millions, or even more data sources.

By enabling extractive Q&A, we enable a more *intelligent* and *efficient* way to retrieve information from what can be massive stores of data.

🌲 Pinecone article:
https://www.pinecone.io/learn/reader-models/

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00:00 Intro
00:13 ODQA Components
03:09 Data Preprocessing
22:35 Fine-tuning