Beginners workshop to fine-tune OpenAI LLM model with enterprise web data in Python
Prodramp
This hands-on workshop shows how to use Langchain LLM application framework with Chroma embedding database to fine-tune an OpenAI GPT-3.5-Turbo LLM model on web data. The final solution returns ChatGPT like interface to your customer web data.
You will also learn:
- Why it is important to fine-tune LLM models with ad-hoc data
- How to use open-source libraries i.e Langchain, ChromaDB
The workshop code:
== Video Timeline == (00:00) Content Intro (00:58) The Problem (04:12) The Solution (06:13) Working Solution Demo (09:10) Understanding Solution (12:12) Open-source libs (14:22) Web Data as source content (12:30) Testing UI (without action) (15:58) Python Libs Installed (17:08) Python Coding Starts (17:27) Setting OpenAI API Key (18:16) Setting Embeddings (20:12) Setting Chunk Splitter (21:02) Setting embeddings Model (21:43) Create & Persist Embeddings (23:30) Test Embeddings Code (26:08) Setting Langchain App (27:30) Adding Query to KB DB (29:18) Testing Query with KB (30:24) Continuous Queries (32:08) Opensource Libs Review (32:41) OpenAI Billing (33:34) Source code (34:00) Recap
=== Open-source Libraries Used: ===
- https://github.com/chroma-core/chroma
- https://github.com/hwchase17/chat-langchain
- https://github.com/openai
Please visit: https://prodramp.com | @prodramp https://www.linkedin.com/company/prodramp
Content Creator: Avkash Chauhan (@avkashchauhan) https://www.linkedin.com/in/avkashchauhan
Tags: #llm #chatgpt #finetunellm #openai #python #ai #langchain #chromadb ... https://www.youtube.com/watch?v=JB1VT7zvEII
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