Tag: PEFT
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LoRA vs Adapter vs Prefix Tuning: PEFT Memory Comparison
Compare LoRA, Adapter, and Prefix Tuning memory usage in this PEFT benchmark. Discover which method delivers the best efficiency trade-offs.
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LoRA ๋ ผ๋ฌธ ๋ฆฌ๋ทฐ: ์์ญ GB ๋ชจ๋ธ์ MB๊ธ ํ๋ผ๋ฏธํฐ๋ก ํ์ธํ๋ํ๋ Low-Rank Adaptation ์์ ๋ถ์
LoRA fine-tunes 175B models with 0.01% trainable parameters. Math behind low-rank decomposition, GPT-3 results, and PyTorch implementation guide.
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LoRA vs QLoRA vs DoRA ์๋ฒฝ ๋น๊ต: ํ๋ผ๋ฏธํฐ ํจ์จ์ ํ์ธํ๋(PEFT) ๋ฉ๋ชจ๋ฆฌ ์ต์ ํ ์ค์ ๊ฐ์ด๋
LoRA uses 60GB GPU, QLoRA needs 16GB, DoRA hits 12GB โ same model quality. Here's the memory breakdown and when to pick each method.