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DeepLearning.AI

Sharon Zhou

Join our new short course, Finetuning Large Language Models! Learn from Sharon Zhou, Co-Founder and CEO of Lamini, and instructor for the GANs Specialization and How Diffusion Models Work. When you complete this course, you will be able to understand when to apply finetuning on LLMs, prepare your data for finetuning, and train and evaluate an LLM on your data. Finetuning allows the model to learn style, form, and can update the model with new knowledge to improve results.

Finetuning Large Language Models

Learn the basics of finetuning large language models and understand its importance in the AI landscape.

Introduction to Finetuning

Understand how to prepare your data for finetuning, including data cleaning and formatting techniques.

Data Preparation

Get hands-on experience in training a large language model using your prepared data.

Model Training

Learn how to evaluate the performance of your finetuned model and make necessary adjustments.

Model Evaluation

Explore advanced finetuning techniques and understand when to use them for optimal results.

Advanced Techniques

Discover practical applications of finetuning in various industries and projects.

Practical Applications

Learn the fundamentals of finetuning a large language model (LLM) with practical experience on real data sets. Understand how finetuning differs from prompt engineering and when to use both techniques.

Individuals who want to understand the techniques and applications of finetuning large language models.

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Finetuning Large Language Models

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