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Update Question_answering_using_embeddings.ipynb
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"Many use cases require GPT-3 to respond to user questions with insightful answers. For example, a customer support chatbot may need to provide answers to common questions. The GPT models have picked up a lot of general knowledge in training, but we often need to ingest and use a large library of more specific information.\n",
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"Many use cases require GPT-3 to respond to user questions with insightful answers. For example, a customer support chatbot may need to provide answers to common questions. The GPT models have picked up a lot of general knowledge in training, but we often need to ingest and use a large library of more specific information.\n",
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"In this notebook we will demonstrate a method for enabling GPT-3 able to answer questions using a library of text as a reference, by using document embeddings and retrieval. We'll be using a dataset of Wikipedia articles about the 2020 Summer Olympic Games. Please see [this notebook](examples/fine-tuned_qa/olympics-1-collect-data.ipynb) to follow the data gathering process."
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"In this notebook we will demonstrate a method for enabling GPT-3 able to answer questions using a library of text as a reference, by using document embeddings and retrieval. We'll be using a dataset of Wikipedia articles about the 2020 Summer Olympic Games. Please see [this notebook](fine-tuned_qa/olympics-1-collect-data.ipynb) to follow the data gathering process."
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