Hugging Face推出aMUSEd模型，幾秒鐘內生成圖像
["Hugging Face推出的aMUSEd模型可以在幾秒鐘內生成圖像，相比其他競爭對手如Stable Diffusion更快。","aMUSEd使用了一種輕量級的文本到圖像模型，基於Google的MUSE模型。","aMUSEd採用了Masked Image Model（MIM）架構，減少了推理步驟，提高了生成速度和可解釋性。","模型可在Hugging Face上的演示中進行嘗試，目前以研究預覽版形式提供，使用OpenRAIL許可證。","aMUSEd生成的圖像質量可以進一步提高，團隊選擇發佈它以“鼓勵社區探索像MIM這樣的非擴散框架用於圖像生成”。"]
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