In addition to using a prompt-based AI chatbot, you can leverage a fine-tuning system to take your chatbot to the next level.
Fine-tuning allows you to customize the chatbot’s responses, making them more relevant, accurate, and aligned with your brand’s unique tone and style.
By fine-tuning, you can build a more tailored experience that addresses your users’ specific needs, ensuring the chatbot provides relevant answers that feel natural and well-organized.
In this section, we will show you to full process.
Well, for fine-tuning you can create data sets in two different methods –
- Train Manually – Here you can create the data set manually with your specific role, queries, and responses.
- Upload JSONL – You can also upload the Data Set in JSONL format.
How to Create the Data Set Manully for Fine Tunning #
First, go to your Hive Support Dashboard. Then navigate to this path – Ai Training > Train AI > Fine Tune. Now choose the training type as Train Manually.

- Provide a relevant Training Name based on your requirements.
- Add a data set based on your training purpose. Such as you want to add some relevant questions about your specific products. Also, you need to specify the role of each data set.
- Add relevant customer questions and AI Responses for each data set. You must add at least 10 data sets for each training. Otherwise, it will not work.
Here is an example of a data set we prepared for training.
| Role/Instructions | Customer Question/Message | AI Response |
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After filling up all the necessary data tap to the Save Training Data button.
Now navigate to the training list menu, and you will be able to see the fine-tuned data set.

As you can see, our training data set is ready. Now tap on the train button of the data set.

It will show you a popup when the training is completed.
Now we can use this data set for fine tuning. For that purpose, go back to the ChatGPT Settings.

- Choose the Fine-tuning as your ChatGPT Training Type.
- Now you need to select the Open AI Model for fine tuning.
- As we already created the data set, it will be visible on the model list. So choose the custom model from here.
- Along with that, you have to set the Max Tokens & Temperature for this model. The token will depend on your API Model tokens. It will determine how many tokens will be used on each response of Chatbot. The temperature will specify the accuracy of each response. By default, you can set the temperature to 1.
After filling up all these necessary data, click on the Save Settings button from the upper section of this page.
How to Upload Data Set in JSONL Format #
Along with data set training, Hive Support also has Upload JSONL functions for pre-generated data sets. To upload the data set, just navigate to the following path –
Train AI > Fine Tune. Choose the Upload JSONL function.

Now upload your pre-generated data set. Finally, click on the Save Training Data. Now you can easily choose this custom API Model from the ChatGPT settings.