As technology advances, more and more businesses and organizations are turning to AI and machine learning to help them work smarter and faster. One of the areas where these technologies are most helpful is in coding. They can help developers and programmers work more efficiently and avoid mistakes. Unfortunately, many of these solutions can be expensive, putting them out of reach for smaller businesses and individuals. That’s why I’m going to teach you how to train an AI to explain code without spending a dime.

In this guide, I’ll show you how to train an AI to explain code like a pro using free tools like PoE.com, ChatGPT, and CodePal. Together, we’ll generate code snippets, explanations, and training data that you can use to train your AI. By the end of this guide, you’ll have a solid understanding of how to train an AI to explain code, and you’ll be able to put these skills to work in your own projects.

Step 1: Access ChatGPT through PoE.com(optional)

This is a website that allows you to access a bunch of cool AI tools, including ChatGPT. It’s a great resource to have on hand when you’re trying to train ChatGPT to explain code.

Once you’re on poe.com, you’ll be able to access ChatGPT and start generating code snippets to work with. You have all the different programming languages to choose from, so you can pick the one that you’re most interested in. This will make it easier for you to train ChatGPT effectively for your programming purposes.

Step 2: Generate Explanations with CodePal

Next, you’ll want to generate some explanations for your code snippets. This is where CodePal comes in. They offer a free credit for new users, which is perfect for our purposes. Use that credit to generate a few explanations for the code snippets you collected earlier.

To use CodePal, simply sign up for a free account and access their AI-powered code explanation tool. Copy and paste your code snippet into the tool and let CodePal generate an explanation for it. You can do this for each of the code snippets in your dataset to get a range of explanations.

Step 3: Train ChatGPT on Code Snippets

Now that you have some code snippets, it’s time to train ChatGPT on them. You can train it on your code snippets by creating a dataset of code snippets and their corresponding explanations.

To create your dataset, you’ll need to save the explanations for each of the code snippets you collected earlier.

Once you have your dataset ready, you can start training ChatGPT.

Step 4: Teach ChatGPT to Explain like CodePal

Now that you have some code snippets and their explanations, it’s time to teach ChatGPT how to explain code like CodePal. This is where the real magic happens. Take those explanations you generated earlier and feed them back into ChatGPT as training data. This will help ChatGPT learn how to generate similar explanations in the future.

To do this, you’ll need to fine-tune ChatGPT on your dataset of code snippets and their corresponding explanations. Fine-tuning is the process of updating the weights of the pre-trained model on your specific dataset.

Once you’ve fine-tuned ChatGPT on your dataset, it’s time to test it out by feeding it a new code snippet and seeing if it can generate an accurate explanation. If it doesn’t, don’t worry! You can continue to fine-tune the model until you get the desired results.