Hello everybody and welcome to Tune GPT. This is something I have been working on for a little while now as an easier way for people to train GPT models with their own custom data. The idea is that these custom models can then be used within your AI deployments, whether that be a chat bot, content generation systems, data analysis models, or anything that ChatGPT can be used for. These fine-tuned models can be used to make the response more suited to your needs.
In this little introduction video, I am going to give you a rundown of just how easy it is to train and deploy a tuned GPT model.
First, you want to come to the website www.tunegpt.app. Click on ‘Train Your First Model’ which will take you to our application. Sign up for an account, make your payment, and provide an OpenAI API key and organization ID. Tune GPT doesn’t charge a markup for training or usage fees. Instead, it directly bills you from your OpenAI account.
Once you have created your account, you will come to the main hub for creating models. Let me show you how to create a tweet sentiment model using data such as this. We have guides on how to format the data. You can download the data as a CSV file. Name your model, for example, ‘Tweet Sentiment Model’, and provide a description of what the model is doing.
You can also customize the number of epochs for training cycles. Currently, we only offer support for the DaVinci model, but we are looking to add support for Ada, Babbage, and Curie soon. If you are struggling with formatting your tweet sentiment, we have a formatting aid box and free resources to help with that.
When you train the model, you will get a price estimate directly from OpenAI. Once you are happy with the estimate, click ‘Train Model’ and your request will be scheduled. After training, you can see the model in the ‘My Models’ section.
You can interact with the model and test its sentiment analysis capabilities. Tune GPT also provides support for embedding the model directly into your applications. You can get the curl command, Python code, and Node.js code for embedding the application.
That’s it! Tune GPT offers an easy and user-friendly way to train and deploy custom GPT models. If you are interested, visit www.tunegpt.app to get started today.
Thank you for listening, and if you have made it this far, I really appreciate it. Show your support by leaving a comment and upvoting the product hunt page. You can find the links in the description. Try Tune GPT for yourself and let me know why you want to try it out. Thank you very much!
