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LoRA (Low-Rank Adaptation) is a popular technique to finetune LLMs more efficiently. This Studio explains how LoRA works by coding it from scratch, which is an excellent exercise for looking under the hood of an algorithm.
← Back to blog How To Finetune GPT Like Large Language Models on a Custom Dataset Posted on May 19, 2023 by Aniket Maurya - Blog, Tutorials Takeaways Learn how to finetune large language models (LLMs) on a custom dataset. We will be using Lit-GPT, an optimized collection of open-source LLMs for finetuning and inference. It supports – LLaMA 2, Falcon, StableLM, Vicuna, LongChat, and a couple of oth
← Back to blog Parameter-Efficient LLM Finetuning With Low-Rank Adaptation (LoRA) Posted on April 26, 2023 by Sebastian Raschka - Articles, Tutorials Key takeaway In the rapidly evolving field of AI, using large language models in an efficient and effective manner is becoming more and more important. In this article, you will learn how to tune an LLM with Low-Rank Adaptation (LoRA) in a computatio
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