Training Thousands of LoRA Adapters at Once
SMRTR summary
Researchers at Osmosis built a system that trains thousands of AI model adapters at the same time, without duplicating the large base model each time. By modifying a framework called Miles with a grouped matrix math technique, one shared base model can run up to 1,536 LoRA adapter instances at once, with each training step completing in under 3 minutes. This dramatically cuts memory waste and speeds up large-scale AI experimentation.
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