QLoRA paper explained (Efficient Finetuning of Quantized LLMs)
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 Published On Dec 28, 2023

QLoRA is the first approach that allows the TRAINING of Large Language Models (LLMs) on a single GPU. It does this by using three contributions namely: 1. a novel NormalFloat data type, 2. Double Quantization, 3. Paged Optimizers.

In this video, we explain the idea behind all three approaches and explain how they are put together to arrive at QLoRA.

⌚️ ⌚️ ⌚️ TIMESTAMPS ⌚️ ⌚️ ⌚️
0:00 - QLoRA
1:34 - Quantization
3:10 - Problem with Quantization
3:50 - Blockwise Quantization
5:42 - Normal Float
6:37 - Double Quantization
7:25 - Paged Optimizers
8:45 - QLoRA Finetuning
9:30 - LoRA vs QLoRA
10:28 - Results

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