Machine Learning
Text Generation for Applications Using Gen AI Studio
Transform your applications with text generation models! Master prompt creation, fine-tuning, and learn how to integrate these advanced AI capabilities into your solutions using Gen AI Studio on Vertex AI
1 Days
Target Audience
Who should attend?
Developers aiming to incorporate Generative AI into their applications.
Machine learning professionals helping build and optimize GenAI-powered solutions
What you'll learn
Explore Generative AI options and interact with foundation models using Vertex AI and Gen AI Studio.Design effective chat prompts and integrate the PaLM API with Python SDK.Fine-tune foundation models to enhance accuracy and relevance.
Prerequisites for Success
Prerequisites for Success
A basic understanding of Python programming or experience leveraging APIs in applications.
• Familiarity with Google Cloud and Vertex AI, as covered in the Google Cloud Fundamentals: Big Data and Machine Learning course.
COURSE AGENDA
Generative AI on Vertex AI
- Overview of Vertex AI on Google Cloud.
- Explore Generative AI options available on Google Cloud.
- Introduction to the course use case, focusing on text generation.
Gen AI Studio
- Introduction to Gen AI Studio as the interface for working with generative models.
- Explore the available models and their use cases.
- Learn how to design and test prompts in the Cloud Console.
- Understand data governance within Gen AI Studio.
- Lab: Get hands-on with Vertex AI and the Gen AI Studio UI.
Prompt Design
- Understand why prompt design is crucial for effective use of generative models.
- Differentiate between zero-shot and few-shot prompting techniques.
- Learn how to provide additional context and tune instructions for better performance.
- Follow best practices for designing prompts.
- Lab: Implement Question Answering with generative models on Vertex AI.
Designing Complex Pipelines
- Branching, Merging & Joining: Learn how to branch, merge, and join different components of a data pipeline.
- Actions & Notifications: Set up actions and notifications to automate tasks and alert users on certain events.
- Error Handling & Macros: Implement error handling strategies and use macros to enhance pipeline flexibility.
- Pipeline Configurations: Explore the configurations for scheduling, importing, and exporting data within pipelines.
Implementing the PaLM API
- Lab: Get started with the Vertex AI PaLM API and Python SDK.
Introduction to the PaLM API for integrating generative models into applications. - Learn to utilize generative models using the Python SDK.
- Understand model parameters for fine-tuning text generation.
- Lab: Use the PaLM API to integrate GenAI into applications.
Fine-tuning Models
- Discover scenarios where model tuning is beneficial.
- Understand the workflow for tuning models to suit specific use cases.
- Learn to prepare your model tuning dataset.
- Create and manage a model tuning job.
- Demo: Learn to fine-tune models for your specific needs.