Train a language model to talk like you | Episode 1 – Introduction
Hi! Welcome to this course. Here, you will learn how to train a language model from scratch. This model will be able to chat like you or anyone else you want.
You will learn how to use chat messages from apps like WhatsApp and Telegram to train your own model. I made this course because I was curious and wanted to understand the full process of training a language model.
In this introductory video, I will explain what you will learn in this course.
Why take this course? One reason is that it is amazing to use math to copy the way someone talks. This could even bring back the way a person spoke, even if they are no longer alive.
Another reason is to learn how to train a language model step by step. We will look at data extraction, data cleaning, tokenization, and more.
Also, I am from Morocco, and we speak Darija. But when we type, we mix French letters with Arabic sounds and sometimes use numbers too! This makes it hard for a language model to understand. So, I want to train a model only on Darija and see if it can learn this language well.
How do we do this? We start by extracting chat data from WhatsApp, Signal, or Telegram. Next, we combine the text into a single file, then encode it using Byte Pair Encoding (BPE) to create a vocabulary.
After that, we build a Transformer model and begin training, splitting the data into training and validation sets. Once trained, we get a base model, which we then fine-tune using a dataset with the target person’s messages. The hardest part is choosing good fine-tuning data, as it directly impacts how the model mimics speech.
The slides and source code are available on GitHub:
https://github.com/ImadSaddik/Train_Y...
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