Building a generative AI model involves several key steps:

• Define the task and gather relevant training data
• Choose an appropriate model architecture (e.g., transformer for text, GAN for images)
• Design the model’s structure, including layers and parameters
• Implement the model using machine learning frameworks like TensorFlow or PyTorch
• Set up the training pipeline and infrastructure
• Train the model on the collected data
• Evaluate and refine the model’s performance
• Deploy the model for practical use