This is Lesson 1 of the Hands-on LLM Course, a FREE hands-on tutorial where you will learn, step-by-step, how to build a financial advisor, using LLMs and following MLOps best practices. This course is not about building a demo inside a Jupyter notebook, but a fully working app, using the
Really good my only comments are - do not to make assumptions about learner’s knowledge especially for beginners. For instance, all terms should be explained in case the learner is not familiar with them. E.g fine-tune, LoRa, CometML etc
Walk through setups with learners explaining each step as you progress. E.g run setup scripts for users to see and code line by like as you explain.
Really good my only comments are - do not to make assumptions about learner’s knowledge especially for beginners. For instance, all terms should be explained in case the learner is not familiar with them. E.g fine-tune, LoRa, CometML etc
Walk through setups with learners explaining each step as you progress. E.g run setup scripts for users to see and code line by like as you explain.
Thanks for the feedback Joshua :-)
In the next lecture, we will go over the code implementation of the fine tuning pipeline, that Paul Iusztin has prepared.