Enhancing Your AI Persona

Overview

Fine-tuning is a critical step in refining your AI persona's behavior, ensuring it consistently aligns with the desired responses and interactions defined by the system prompt. The fine-tuning process in the Hub allows you to introduce new training sets that reinforce the persona's behavior without altering the system prompt. This approach helps maintain the stability of the AI’s identity while allowing you to make precise adjustments to its behavior.

Step 1: Selecting the Expert and Model

Choosing the Expert and Model

Before you begin fine-tuning, start by selecting the AI persona (expert) you wish to refine within the Hub:

1. Select the Expert: Choose the specific AI persona that requires fine-tuning. This persona will be the focus of the training sets you’re about to create or import.
2. Select the Model: Depending on the version of the Hub and the available features, you may also select the underlying Language Learning Model (LLM) that powers the expert. Choosing the appropriate model is essential as it influences how the AI processes and responds to the training data.

Step 2: Generating Training Data with F2TD

Using the F2TD (First-to-Data) Feature

The Hub provides a powerful tool called F2TD (First-to-Data), which is designed to help you create training data from any information you provide. This feature is especially useful for generating "situations," which are generalized training scenarios beyond typical conversations. These situations can include multimodal behavior training or automation tasks, making the AI more versatile and contextually aware.

Steps to Generate Situations:

1. Input Information: Enter the information or scenarios you want to use for training into the provided text area. This can include specific responses, actions, or behaviors you want the AI to learn.
2. Generate Situations: Click the "Generate Situations" button. The AI will process the input and create various situations that the expert can use as training data. These situations serve as the foundation for refining how the AI responds to different prompts and tasks.

What Are Situations?

• Situations: Unlike traditional conversations, situations represent a broader set of interactions or tasks. They are designed to train the AI on various behaviors, including multimodal tasks and automation processes. This general approach ensures that the AI can handle a wide range of scenarios beyond simple text-based interactions.

Step 3: Utilizing Favorite Situations

QA Marking Sessions and Importing Data

Beyond generating new situations, the Hub allows you to further refine your AI persona by using previously created situations or importing data from other sources, such as ChatGPT:

1. Start a QA Marking Session: In the Chat section of the Hub, you can select your favorite situations for fine-tuning. Initiate a QA (Quality Assurance) marking session to evaluate and refine these situations, ensuring they accurately guide the AI’s responses.