Apple MLX Fine Tuning: Complete Crash Course for Beginners
🚀 Dive deep into the world of machine learning fine-tuning with our comprehensive guide on using the MLX package to transform natural language questions into SQL queries! 🚀
In this video, we'll take you through every step of the process, from preparing your dataset to training and evaluating your model, and finally, uploading it to Hugging Face. Discover how to leverage the MLX package on your Mac to fine-tune a massive 7 billion parameter model, specifically tailored to convert questions directly into SQL queries.
🔍 What You'll Learn:
How to set up and prepare your data for fine-tuning.
Step-by-step instructions to train and evaluate your ML model.
Tips for uploading your finely-tuned model to Hugging Face for community use.
🛠 Tools and Commands:
MLX and Qora for running and fine-tuning large language models.
Practical use of WikiSQL dataset for SQL query generation.
Commands for cloning repositories, creating environments, and installing requirements.
💡 Whether you're looking to enhance your AI projects or dive into machine learning model fine-tuning, this video has got you covered. Make sure to subscribe and hit the bell icon to stay updated on all things Artificial Intelligence. Like this video to help spread the knowledge!
🔗 Resources:
Patreon: / mervinpraison
Ko-fi: https://ko-fi.com/mervinpraison
Discord: / discord
Twitter / X : / mervinpraison
Code: https://mer.vin/2024/02/mlx-mistral-l...
Timestamps:
0:00 Introduction to MLX Fine-Tuning
0:02 Setting Up for Fine-Tuning
1:02 Preparing Your Data
1:34 Installing MLX Requirements
2:01 Training the ML Model
2:55 Evaluating Model Performance
3:00 Data Folder Structure and Content
3:57 Training Data Breakdown
4:26 Starting the Training Process
5:17 Training Completion and Performance Review
5:38 Fine-Tuning Results
6:20 Uploading to Hugging Face
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