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Why you have decided to use empty prompt "" when you need to use the unet to build the features from the noise image? input_ids_for_encoder = tokenizer( "", # args.prompt_template.format(placeholder_token=args.domain_class_token), padding="max_length", truncation=True, max_length=tokenizer.model_max_length, return_tensors="pt" ).input_ids
We know that the image would be something like "a photo of args.domain_class_token" so I'm not sure if this can have an impact on the pretraining
The text was updated successfully, but these errors were encountered:
@Actis92 Hi sorry for the late reply. This is actually a good point! You can definitely experiment this. In fact, you can see this line to show that I was about to try it. But, I ended up to use the null string because the author apparently used it.
Why you have decided to use empty prompt "" when you need to use the unet to build the features from the noise image?
input_ids_for_encoder = tokenizer( "", # args.prompt_template.format(placeholder_token=args.domain_class_token), padding="max_length", truncation=True, max_length=tokenizer.model_max_length, return_tensors="pt" ).input_ids
We know that the image would be something like "a photo of args.domain_class_token" so I'm not sure if this can have an impact on the pretraining
The text was updated successfully, but these errors were encountered: