Overview
This course on Prompt Templates for GPT 3.5 and other LLMs aims to teach learners about PromptTemplates, FewShotPromptTemplates, and example selectors in LangChain. The course covers the importance of prompts, prompt structure, setting up Langchain code, utilizing PromptTemplates, implementing few-shot learning with Large Language Models (LLMs), exploring different example selectors based on length, and providing final insights on prompts and LangChain. The teaching method involves video tutorials and practical demonstrations. This course is intended for individuals interested in prompt engineering for LLMs like OpenAI's GPT 3, Cohere, and Hugging Face's OS alternatives, as well as those looking to build apps and pipelines around Large Language Models for various applications such as chatbots, Generative Question-Answering (GQA), and summarization.
Syllabus
Why prompts are important
Structure of prompts
Langchain code Setup
Langchain's PromptTemplates
Few shot learning with LLMs
Few shot prompt templates in Langchain
Length-based example selectors
Other Langchain example selectors
Final notes on prompts + Langchain
Taught by
James Briggs