What is model parallelism?
An example of an AI chatbot conversation about model parallelism in AI and machine learning.
Can you explain what model parallelism is?
Sure! Model parallelism is a technique used in machine learning where different parts of a model are distributed across multiple devices.
Why is model parallelism important?
It's important because it allows for training larger models that wouldn't fit into the memory of a single device, improving efficiency.
How does it differ from data parallelism?
Model parallelism splits the model itself, while data parallelism splits the data across multiple copies of the model.
Can you give an example of when to use model parallelism?
Certainly! It's often used in deep learning for large neural networks, like GPT-3, where different layers can be on different GPUs.
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