Comments (2)
可以看我们之前的文章cogview2,http://github.com/THUDM/CogView2 ,是你说的用token的语言模型的思路,结合了双向理解和生成,你可以用此思路和预训练llama结合一下。本仓库直接使用图像的feature,不需要自回归生成图像。
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可以看我们之前的文章cogview2,http://github.com/THUDM/CogView2 ,是你说的用token的语言模型的思路,结合了双向理解和生成,你可以用此思路和预训练llama结合一下。本仓库直接使用图像的feature,不需要自回归生成图像。
想再请教一下代码细节,我看代码里图片有一个 image_length
默认为 32,这个是图片的 patch size 吗?然后图片经过 ViT 和 Q-Former 以后又进入了一个投影层转换维度是不是也可以看做是和 word_embedding 对齐的操作?然后视觉模型里面的 Mixin
这个名字是什么意思呀?
感谢~
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Related Issues (20)
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