GENERATING CUSTOM CHATGPT MODEL - AI FINE TUNING

FINE TUNING CONCEPTS

Fine-tuning refers to using the weights of an already trained network as the starting values for training a new network/model.

Using a model pre-trained with a large dataset for solving a problem similar to the one we’re dealing with. This is especially useful if we don’t have a lot of data for the task at hand, but a ready-to-use model for a related problem with a lot of data is available.

NEURAL NETWORKING

A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.?

HOW NEURAL NETWORK WORKS ?

An artificial neural network is made of artificial neurons that work together to solve a problem. Artificial neurons are software modules, called nodes, and artificial neural networks are software programs or algorithms that, at their core, use computing systems to solve mathematical calculations.

A basic neural network has interconnected artificial neurons in three layers:

Input Layer

Information from the outside world enters the artificial neural network from the input layer. Input nodes process the data, analyze or categorize it, and pass it on to the next layer.

Hidden Layer

Hidden layers take their input from the input layer or other hidden layers. Artificial neural networks can have a large number of hidden layers. Each hidden layer analyzes the output from the previous layer, processes it further, and passes it on to the next layer.

Output Layer

• The output layer gives the final result of all the data processing by the artificial neural network using the activation functions. It can have single or multiple nodes For instance, if we have a binary (yes/no) classification problem, the output layer will have one output node, which will give the result as 1 or 0.
• The more no. of times the model will be trained, the best results are expected.

EPOCS CONCEPT

• The number of epochs is a hyper parameter that defines the number times that the learning algorithm will work through the entire training dataset.
• One epoch means that each sample in the training dataset has had an opportunity to update the internal model parameters.?

SOFTMAX ACTIVATION FUNCTION

• It is usually placed as the last layer in the deep learning model.
• The Softmax regression is a form of logistic regression that normalizes an input value into a vector of values that follows a probability distribution whose total sums up to 1.

CREATING OWN CUSTOM CHATGPT MODEL

PREPARING DATASET -

1. Create your own training data in .csv format. The ChatGPT models accepts the training data in .json format and provides a feature to convert the data in the required format.
2. Or the pre-created dataset can be downloaded from https://www.kaggle.com/

SETTING THE REQUIRED PARAMETERS TO GET STARTED -

A OpenAI_API_key will be required to make connection with our account of OPENAI website and once, this is done we are good to proceed with fine tuning and creating the custom model generation.

TRAINING THE CUSTOM CHATBOT

The generation of Custom Chatbot will utilze the functioning of neural network (explained above) and more no of epocs will lead to the better results.

START USING THE GENERATED CUSTOM MODEL FOR PROMPT -

Once the fine-tuned model gets created, it is ready to use for prompt completion via CLI or GUI either.

Below are the snippets -

DALL-C FEATURE OF OPANAI

DALL·E 2 is a new AI system that can create realistic images and art from a description in natural language

Dall-c feature of OPENAI tool allows to generate the images using the AI concepts at backend.

Example -

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