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Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation)
Things I Learned From Hundreds of Experiments
No starch
How important
How do you select
How to avoid
How does
Full finetuning
Layer wise optimal rank
Brief introduction
Normal floats
Parameter models
Dataset perspectives
Less is more
Scalable stochastic second order optimizer
Language model pre training
Layer wise optimal rank adaptation
Machine learning
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