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would this outperform the api<>instruction pairs stuffed into a vector db and running an retrieval augmented chain of thought on openai

this is how openai plugins work right ?



> Gorilla, a finetuned LLaMA-based model that surpasses the performance of GPT-4 on writing API calls. When combined with a document retriever, Gorilla demonstrates a strong capability to adapt to test-time document changes, enabling flexible user updates or version changes

keywords "finetuned" and "document retriever"

So it's fine tuned to create API calls but still uses a db to fetch the API shape.

They also say that they're doing a "retriever aware" training, meaning passing examples in the dataset that point out that a document with the API shape is gonna follow the question, in the hope that the model learns to always check on that before answering.




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