Explore a comprehensive tutorial on evaluating the performance of language models like OpenAI's GPT-3 using Langchain and custom prompts. Learn to create environments, install necessary packages, and review code for LLM question-answering tasks. Discover how to craft custom prompts for LLM evaluation and analyze code for agent evaluation with tools. Gain insights into using datasets from Huggingface and leverage Langchain's evaluation capabilities. Follow along with a detailed timeline, from introduction and demo to final code review, to enhance your understanding of LLM performance assessment.
Langchain- Auto Evaluate LLMs and Agents- OpenAI GPT-3 Evaluation Using Langchain and Custom Prompts
Overview
Syllabus
intro and demo
Creating environment and pip installs
Code review for llm QA
Custom prompt for llm eval
Code review for Agent with tool eval
Final Code review
Taught by
echohive
Related Courses
-
ChatGPT: GPT-3, GPT-4 Turbo: Unleash the Power of LLM's
-
Langchain Summary and QA with Chromadb Using OpenAI Embeddings and GPT-3 With Token Count
-
Langchain Chains and Chaining Explained - GPT-3 LLM Tutorial with Streaming Responses, Multi Input
-
Langchain ChatGPT Your Documents Challenge Part 2 with GPT-3 and OpenAI Embeddings and Streamlit UI
-
LangChain Agents Deep Dive with GPT 3.5 - LangChain
-
Chatbot with LangChain Agents + GPT 3.5
