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Seth Kramer
Fine tuning with OpenAI
In this course, you'll learn how to fine-tune with OpenAI and GPT. You'll understand the best practices and fine-tune your own model!
Seth Kramer
Learn the stack
Follow the tools and the decisions, not just the clicks.
Ship your version
Use the course as a template for your own product.
What you'll get
Build the project. Keep the skill.
Every course ends with a shipped artifact and a reusable pattern. Faster builds, smarter decisions, real products.
Learn the exact stack used to ship the project
Understand the build decisions, not just the steps
Walk away with a pattern you can reuse on your own
Overview
This course will teach how to fine-tune pre-trained OpenAI models for specific tasks and use cases. Students will learn how to select the appropriate model architecture and how to prepare and format data for fine-tuning.
They will also learn how to train and evaluate the fine-tuned model, as well as techniques for troubleshooting and improving performance.
By the end of the course, students will have the skills and knowledge necessary to fine-tune OpenAI models for a variety of natural language processing tasks such as text classification, language translation, and text generation.
What you'll learn
- Learn use-cases for fine-tuning
- Learn best practices for creating your own model
- The process of how fine-tuning works
- How to create fine-tuning datasets
- How to create your own fine-tuned AI model
Who this is for
- Entrepreneurs
- Marketers
- Data Scientists
- Anyone interested in using the state-of-the-art language models for their projects
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