How To Fine-Tune An LLM for A Question Answer (QA) Task Locally
Last Updated on July 15, 2023 by Editorial Team
Author(s): Dr. Mandar Karhade, MD. PhD.
Originally published on Towards AI.
A practical step-by-step guide to Extracting information from your custom data by asking questions
There are three main types of question-answering tasks.
Extractive QA: It is the task in which systems extract the answer to the question from a given text (fed text). This is the most common form of the QA system and is part of most general-purpose Automation systems like Alexa or Google Search, etc.
Open Generative QA: It is a task in which the system generates answers in the natural language. The focus is on more generative AI to make the answer feel more natural than purely information extraction. However, the Open generative QA tasks need the context to be provided, and the… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
