LLM Fine-Tuning and LoRA: Making Large Models Work for You
As powerful as large language models (LLMs) like GPT, LLaMA, and Mistral are, they’re still general-purpose. If you want to make them truly useful for your domain—whether it’s legal documents, financial analysis, or German tax law—you need to fine-tune them. And thanks to a technique called LoRA (Low-Rank Adaptation), you can now fine-tune LLMs with a fraction of the data, compute, and cost. 🔧 What is Fine-Tuning? Fine-tuning is the process of continuing the training of a pre-trained LLM on your own dataset so that it learns domain-specific patterns, vocabulary, tone, or tasks. ...