【Complete Edition】Gpt-Oss 20B / Gemma 3N Series Fine-Tuning

Master Next-Gen LLM Development from Zero with Google Colab

What you'll learn

Fine-tune GPT-OSS 20b / Gemma 3n 4b / Gemma 3n 270m using your own dataset (hands-on)

Master Core Concepts of GPT-OSS: Gain a deep understanding of cutting-edge models like gpt-oss 20B and the Gemma 3N series, including their unique architectures

Implement Parameter-Efficient Fine-Tuning (PEFT)

Leverage Unsloth for Peak Performance

Execute Advanced Data Preparation

HuggingFace TRL SFTTrainer

Adapt Models to Specialized Domains

Control AI "Reasoning Effort" of gpt-oss

Work with Multimodal Inputs using Gemma 3n

Run Efficient Inference with Unsloth

Save and Prepare Models for Deployment

Requirements

Primary Requirement: A Computer with an Internet Connection

Google Account

A Desire to Learn generative AI

Basic Python Programming(Beneficial, Not Required)

Familiarity with AI Concepts (Beneficial, Not Required)

Description

【Complete Edition】gpt-oss 20B / Gemma 3n Series Fine-tuning Masterclass Master Next-Gen LLM Development from Zero with Google ColabThe AI Revolution is Here – And It's AccessibleMyth: You need expensive hardware for Large Language Models. Not anymore.This comprehensive course covers fine-tuning OpenAI's open-source gpt-oss 20B and Google's Gemma 3n series (4B/270M). Start free with Google Colab; upgrade to Pro ($9.99/month) for advanced features.Why This Course?Three Models in One Course:gpt-oss 20B: OpenAI's open-source model. Apache 2.0 licensed. 32-expert MoE architecture. Adjustable reasoning. Runs on 16-24GB VRAM.Gemma 3n 4B: Multimodal with vision, audio, and cross-modal reasoning. Production-ready.Gemma 3n 270M: Efficient for edge devices. Great for prototyping.Accessibility:Free Colab (T4 GPU, 16GB): Inference, demos, basic fine-tuning.Pro Colab (L4 GPU, 24GB): Full fine-tuning, optimization.Learn 80% without spending.100% Verified:Notebooks tested August 19, 2025. Works on Free/Pro. Troubleshooting included.Curriculum (8 Modules):Introduction & Setup: Architectures, Colab setup, Unsloth.Technical Deep Dive: MoE, MXFP4 quantization, reasoning controls.gpt-oss 20B: Loading, LoRA fine-tuning, multi-language, memory optimization.Gemma 3n 4B: Multimodal preprocessing, alignment, integration.Gemma 3n 270M: Efficient fine-tuning, edge deployment.Advanced Techniques: Datasets, formatting, SFTTrainer, tuning.Applications: Problem solver, customer service, assistants.Troubleshooting: VRAM, convergence, optimization.Real Results:Customer Bot: 42% to 89% accuracy.Summarization: 0.41 to 0.68 ROUGE.Q&A: 65% to 93% resolution.API Savings: $30,000 to $3,000/month.Investment:Beginner: Free Colab – Inference, basic.Professional: Pro Colab $9.99/mo – Full training.Saves 99% vs. traditional costs.Who Should Take:Beginners, developers, researchers, data scientists, students, AI enthusiasts.Prerequisites:Basic Python (helpful).Google account.Curiosity.Not needed: Advanced math, ML experience, hardware, Pro subscription.Why Start Today?Zero-risk with free Colab.Master new models early.Immediate insights.Top skill in tech.Learning Journey:Week 1 (Free): Run 20B model, MoE, inference.Week 2: Fine-tuning, LoRA, multimodal.Week 3+: Full training, deployment.Instructor: Joshua K. CageLLM bestselling author.30,000+ students.AI education pioneer.Global: Students from 50+ countries. English materials, clear code.Start Now:Free: Open Colab, load notebooks, run LLM in 5 minutes.Pro: Upgrade for fine-tuning.Achievements:1 Hour: Run 20B model.1 Day: MoE/quantization.1 Week: First fine-tuning.1 Month: Production AI.No need for hardware, experience, degrees, budgets. Just this course, browser, curiosity.Join the AI RevolutionEnroll Now - Start TodayLifetime access, updates, certificate, 30-day guarantee. Transform your career. Start free.

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Technical Background

Lecture 2 GPT OSS 20B v.s. 120B / OSS License / MoE Architecture/MXFP4 /Reasoning Effort

Section 3: Environmental Setup (Google Colaboratory)

Lecture 3 Environmental Setup (Google Colaboratory)

Section 4: Installing the modules needed to fine-tune GPT-OSS 20b

Lecture 4 Installing the modules needed to fine-tune GPT-OSS 20b and load the model

Section 5: LoRA Adaptation

Lecture 5 LoRA Adaptation

Section 6: Reasoning Effort

Lecture 6 Reasoning Effort of gpt-oss

Section 7: Prepare multilingual thinking dataset from huggingface dataset

Lecture 7 Prepare multilingual thinking dataset from huggingface dataset

Section 8: Fine-tune gpt-oss with multi thinking dataset using T4/L4 GPU

Lecture 8 Fine-tune gpt-oss with multi thinking dataset using T4/L4 GPU

Section 9: Use Micro-wave related 5 FAQ for fine-tuning

Lecture 9 Fine-tuning using manually created microwave oven product support FAQ data

Section 10: Inference Test

Lecture 10 Inference Test

Section 11: Gemma 3n 4b Fine runing hands-on

Lecture 11 Gemma 3n 4b Fine runing hands-on

Section 12: Gemma 3n 270m fine tuning hands-on

Lecture 12 Gemma 3n 270m fine tuning hands-on

Section 13: Summary and frequently asked questions

Lecture 13 Summary and frequently asked questions

Passionate AI Hobbyists & Enthusiasts,Tech Entrepreneurs & Product Managers,AI Researchers & Data Scientists,AI/ML Engineers & Software Developers,Passionate about open-source LLMs? You're in the right place