Learn how to fine-tune large language models (LLMs) locally using aiDAPTIV+ with both the Pro Suite Graphical User Interface and the Command Line Interface. This repository contains all lesson materials, datasets, code examples, and project files to learn aiDAPTIV+.
This hands-on curriculum is designed to teach you how to:
- Fine-tune LLMs on your own hardware or a provided remote AI Training PC (AITPC).
- Optimize GPU VRAM usage with aiDAPTIVCache.
- Use both GUI and CLI workflows for training and inference.
- Apply fine-tuning to real-world datasets such as company handbooks or public figure transcripts.
The course includes about 2 hours of recorded, follow-along video content, but the full experience takes around 12 hours to complete.
Most of that time is spent running fine-tuning jobs, so you don’t need to stay at your computer while training is in progress.
Whether you’re a developer, researcher, or student, you’ll gain practical skills to run on-prem AI cost-efficiently and securely.
To take this course, you’ll need access to an AI Training PC.
👉 Click here to request remote access
(Your request will be reviewed, and credentials will be sent to you once approved.)
💻 Step 2: Alternatively, use your own system
If you already have an aiDAPTIV+ installed on your own hardware, you can skip the reservation form.
👉 Installation instructions for aiDAPTIV+
✅ Once you have either remote or local access, you’re ready to begin the lessons.
| Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson |
|---|---|---|---|---|
| 01 | Welcome & Introduction | Introduction | Overview of the aiDAPTIV+ platform, course structure, and how to get started. | lesson video |
| 02 | Accessing the AI Training PC | Introduction | Learn how to request, connect to, and work with the remote AITPC for course exercises. | lesson video |
| 03 | Fine-Tuning via Pro Suite GUI | GUI Based | Use the aiDAPTIV+ Pro Suite GUI to fine-tune a custom LLM using the Phison Employee Handbook dataset. | lesson video |
| 04 | Instruction Fine-Tuning | CLI Based | Learn how to fine-tune a model on instruction–response datasets for more structured outputs. | lesson video |
| 05 | Speaking Style Model | CLI Based | Fine-tune an LLM to adapt its output style for different tones, audiences, and communication needs. | lesson video |
| 06 | RAFT Dataset Generation | CLI Based | Generate retrieval-augmented datasets to improve factual grounding and domain specialization. | lesson video |
| 07 | LLM as a Judge | CLI Based | Use LLMs to evaluate and grade outputs from other models with rubrics. | lesson video |
| 08 | Vision Function Calling | CLI Based | Explore how Vision-Language Models (VLMs) can analyze images and trigger structured functions. | lesson video |
We’d love to hear your feedback on the aiDAPTIV+ Training Course!
Please use our feedback form to share your thoughts, suggestions, or issues:
👉 aiDAPTIV+ Training Course Feedback Form