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qlora

AI, ML & GenAI interview questions tagged qlora, across every topic.

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Concepts behind "qlora"

The curriculum that explains the ideas these questions test.

Core
🧠 Foundations of LLMs & GenAISign in
LoRA and Parameter-Efficient Fine-TuningFull fine-tuning updates all of a model's weights, costly in compute and memory and leaving a full-size copy per task. LoRA freezes the base model and trains small low-rank adapter matrices, dropping trainable parameters by orders of magnitude while matching most of full fine-tuning's quality. QLoRA layers on 4-bit base quantization to fit huge models on one GPU. AI, ML, and GenAI interviews probe it because PEFT is how teams actually fine-tune, and because LoRA adapters make serving hundreds of variants cheap.
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