Huawei’s DiffFit Unlocks the Transferability of Large Diffusion Models to New Domains | Synced

In the new paper DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning, a Huawei Noah’s Ark Lab research team introduces DiffFit, a parameter-effic...

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Source: Synced | AI Technology & Industry Review

In the new paper DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning, a Huawei Noah’s Ark Lab research team introduces DiffFit, a parameter-efficient fine-tuning technique that enables fast adaptation to new domains for diffusion image generation. Compared to full fine-tuning approaches, DiffFit achieves 2x training speed-ups while using only ~0.12 percent of trainable parameters.

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