Arxiv Dives - How LoRA fine-tuning works
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Every Friday at Oxen.ai we host a paper club called "Arxiv Dives" to make us smarter Oxen 🐂 🧠. We believe diving into the details of research papers is the best way to build fundamental knowledge and keep up with the bleeding edge. If you would like to join the discussion
  • HighFreqAsuka@alien.topBEnglish
    1·
    11 months ago

    LoRA fine tuning is an incredibly simple idea. For each matrix you want to fine-tune, introduce a low rank matrix ΔW = BA where the inner dimension is r << d, and compute (W + ΔW)x. Freeze all pretrained parameters and only update B and A. B is initialized to 0 so that the initial model is equal to the pretrained model. After training, you can also write V = W + ΔW to preserve latency.

    Saved you a click.

    • residentmouse@alien.topBEnglish
      1·
      11 months ago

      Well now I feel almost obligated to click - is the part of the title “deep dive” completely misleading or is the post really just a LoRA explanation?