
GPU Considerations, Labeling Privacy, Rapid Fine Tuning, and the Role of Private Eval Pipelines to Benchmark New Models
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Navigating GPU Transition and Importance of Provider Support
This chapter delves into the intricacies of using GPU providers for machine learning, focusing on the difficulties of switching options and the vital role of provider support. Personal anecdotes illustrate the challenges of managing large clusters and the impact on model training and data operations.
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