DeepLearning.AI
Learn how to compress models with the Hugging Face Transformers library and the Quanto library. This course covers linear quantization and downcasting techniques to make generative AI models more efficient and accessible.
In this course, you will learn how to compress models using linear quantization and downcasting techniques. You will gain a foundation in quantization methods, enabling you to optimize generative AI models for better performance on various devices. By the end of the course, you will be able to apply these techniques to your own models, making them more efficient and accessible.
Machine Learning Enthusiasts
Individuals with a basic understanding of machine learning concepts who want to learn about model quantization.
AI Developers
Developers interested in optimizing generative AI models for better performance and efficiency.
Data Scientists
Data scientists looking to make AI models more accessible and efficient for various devices.
This course will teach you essential quantization techniques to optimize generative AI models, making them more efficient and accessible. Ideal for beginners and professionals looking to enhance their AI skills and improve model performance.
1 / 2
Basic understanding of machine learning concepts
Some experience with PyTorch
Younes Belkada
Instructor, DeepLearning.AI
Younes Belkada is an instructor at DeepLearning.AI, focusing on Machine Learning and Data Science topics.
Marc Sun
Machine Learning Engineer, Hugging Face
Marc Sun is a Machine Learning Engineer at Hugging Face, an open-source team dedicated to democratizing machine learning. He is also an instructor at DeepLearning.AI.
Cost
Free
Duration
Dates
Location