this post was submitted on 27 Nov 2023
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Machine Learning
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Nice! Thank you for your work.
Regarding the video.
Q1) minute 14:14 Finetuning into an Assistant, when you have multiple tasks / datasets with diverse outputs how is training performed ? Are all datasets combined in a single training ? Or Is finetuning done over a previous finetuning ? Or the question is parsed and sent to a specific model ?
Q2) minute 27:43 Tool Use (Browser, Calculator, etc. ) Anyone has links for similar implementations for llama and how is done or what kind of tech/frameworks are used ?
The naive way is to use langchain, but that's hit and miss for several reasons, and whatever you build will be held together by duct tape and prayers. Alternative frameworks include Haystack and Griptape.
I've found that for local models the best tool-usage you can get is by using an advanced control library. This gives you a lot of flexibility in organising the prompts and "helping" the local models a lot. Guidance and LMQL are two such libraries.
Thanks. Guidance seems a good fit I'll start looking for more info.