We can use this model = UNet2DConditionModel.from_pretrained('path_to_model')
to load a Unet model and then we can put this in a DiffusionPipeline
.
I have trained a Unet from scratch in Pytorch with Conv2d(in_channels, out_channels, kernel_size, etc)
and saved it into a .pt file.
Is there a way where I can load this .pt file in diffusers UNet2DConditionModel.from_pretrained('path_to_.pt_file')
and then add it into the pipeline?