Decoder weights of FDDA. FDDA post-trains the tokenizer decoder of a frozen latent generative model with a Fréchet distance loss on generated samples. Code, installation and evaluation: Each checkpoint stores the tokenizer state dict with the adapted decoder ({"model", "epoch"}) and is used with the generator in --generatorname. ImageNet 256x256, 50,000 generated samples. gFD r6 is the mean over six representation spaces (Inception-v3, ConvNeXt-v2, DINOv2, MAE, SigLIP2, CLIP) of FD divided by the FD of the ImageNet validation set. beforegeneratorside/ /: decoders adapted to the
Independent publisher
Zhu
jiajunzhu
NLP
Models in Library1
Datasets in Library0
Models on Hugging Face4
Followers1
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