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>I wouldn't use either of them for RAG What's RAG?
by rnd0 3y ago
>I wouldn't use either of them for RAG
What's RAG?
- andy99 3y agoRetrieval augmented generative, basically giving it some text passage and asking questions about the text.
- dmezzetti 3y agoIf you want more on RAG with a concrete example: https://neuml.hashnode.dev/build-rag-pipelines-with-txtai https://neuml.hashnode.dev/build-rag-pipelines-with-txtai
- sp332 3y agoSince the models have a limited context size, you pre-process a bunch of data that might be related to the task (documentation, say) and generate a semantic vector for each piece. The when you ask a question, look up just the few pieces that are semantically most simlar and load them into the context along with the question. Then the LLM can generate a new answer with the most relevant pieces of data.