March 9, 2024, 3 p.m. | Shaw Talebi

Towards Data Science - Medium towardsdatascience.com

A beginner-friendly introduction w/ Python code

This article is part of a larger series on using large language models in practice. In the previous post, we fine-tuned Mistral-7b-Instruct to respond to YouTube comments using QLoRA. Although the fine-tuned model successfully captured my style when responding to viewer feedback, its responses to technical questions didn’t match my explanations. Here, I’ll discuss how we can improve LLM performance using retrieval augmented generation (i.e. RAG).

The original RAG system. Image from Canva. …

ai article beginner data science editors pick feedback introduction language language models large language large language models llm llms machine learning match mistral part practice python qlora questions rag responses series style technical youtube

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US