Learning Notebook - David Rostcheck
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Many use cases such as building a chatbot require text (text2text) generation models like BloomZ 7B1, Flan T5 XXL, and Flan T5 UL2 to respond to user questions with insightful answers. The BloomZ 7B1, Flan T5 XXL, and Flan T5 UL2 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. In this notebook we will demonstrate how to use BloomZ 7B1, Flan T5 XXL, and Flan T5 UL2 to answer questions using a library of documents as a reference, by using document embeddings and retrieval. The embeddings are generated from GPT-J-6B embedding model. This notebook serves a template such that you can easily replace the example dataset by your own to build a custom question and asnwering application.
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