VQ-Diffusion：基於離散擴散模型的文本到圖像生成技術
Original: VQ-Diffusion
In late 2022, while continuous-space diffusion models represented by Stable Diffusion were stealing the spotlight, diffusion models…
Hugging Face 介紹了微軟開發的 VQ-Diffusion 模型，這是一種基於離散空間的文本到圖像生成技術。與傳統在連續空間運作的擴散模型不同，它結合了 VQ-VAE 的離散 Token 表示法與擴散模型，有效解決了自迴歸模型的誤差累積問題。開發者與研究人員可以透過 Hugging Face 的 `diffusers` 套件輕鬆調用此模型進行高效的影像生成。
In late 2022, while continuous-space diffusion models represented by Stable Diffusion were stealing the spotlight, diffusion models operating in discrete space were also demonstrating tremendous potential. Hugging Face published this article introducing VQ-Diffusion (Vector Quantized Diffusion Model), a novel text-to-image generation model proposed by Microsoft Research Asia and other institutions.
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