I Thought Fine-Tuning LLMs Needed Expensive GPUs. I Was Wrong.

Yesterday I fine-tuned a 1.1B parameter language model using QLoRA on consumer hardware. And honestly? The hardest part wasn’t training. It was debugging everything around it. I started with a simple goal: “understand how LLM fine-tuning actually works.” A few hours later I was deep into: NF4 quantization LoRA internals tokenization chat templates VRAM optimization adapter injection FastAPI serving Redis caching Qdrant RAG pipelines and dependency version warfare This was the stack: TinyLla...