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Handling Multi-Terabyte LLM Checkpoints // Simon Karasik // #228
MLOps.community
Fine-tuning Models with Fewer GPUs
Fine-tuning a model requires fewer GPUs compared to the initial pre-training phase which may involve using thousands of GPUs. Fine-tuning involves smaller datasets, typically containing only thousands of rows, unlike pre-training which could involve billions of rows. Even though the model size remains the same, the workload changes as the data is now processed by fewer machines instead of a large cluster. This shift in workload impacts the cloud requirements, with a focus on scalability and the ability to handle the load from fewer machines efficiently, rather than distributing it across a large number of machines.
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