<ul><li>LoRA is a method of optimising large language models (LLMs) by tweaking only a small part of the model instead of fine-tuning all parameters.</li><li>LoRA involves freezing the original model weights and injecting low-rank matrices to reduce compute and memory usage during training.</li><li>The researchers focused on adapting Transformer layers and achieved significant results, reducing VRAM consumption by a large margin.</li><li>LoRA demonstrates better scalability and task performance compared to other existing methods, proving the importance of optimised and efficient models in AI.</li></ul>

The LoRA Trick That’s Quietly Revolutionizing LLM Fine-Tuning

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