IT Career Guides & Free Resources
Expert roadmaps, tutorials, salary guides and interview prep across Data Science, Generative AI, Python, Cloud & Analytics — written by GloryTecks trainers in Hyderabad.
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Fine-Tuning vs RAG: Which Should You Choose?
Fine-tuning and RAG are often presented as rivals. They change different things: retrieval gives a model facts to read, and fine-tuning changes how it behaves. This guide shows the difference with a test on a local model, summarises the research and gives an order to try things in.
LoRA and QLoRA: Efficient Fine-Tuning Explained
Full fine-tuning retrains every weight in a model. LoRA freezes them all and trains a small add-on instead, and QLoRA shrinks the frozen model to 4 bits so it fits on one graphics card. This guide explains both and runs LoRA for real: 294,912 trainable parameters out of 124 million, and an adapter of 1.2 MB.