Exception training model: ' Some tensors share memory, this will lead to duplicate memory on disk and potential differences when loading them again: [{'encoder.conv_in.weight', 'decoder.up_blocks.1.upsamplers.0.conv.weight', 'decoder.up_blocks.3.resnets.0.conv_shortcut.weight', 'decoder.up_blocks.3.resnets.0.norm1.weight', 'encoder.mid_block.resnets.1.norm1.weight', 'decoder.mid_block.resnets.0.conv1.bias', 'encoder.down_blocks.1.resnets.0.norm1.bias', 'encoder.conv_norm_out.weight', 'decoder.up_blocks.2.resnets.0.norm1.weight', 'encoder.down_blocks.3.resnets.1.conv1.bias', 'encoder.down_blocks.0.resnets.1.norm2.bias', 'encoder.mid_block.resnets.0.norm1.bias', 'decoder.up_blocks.1.resnets.1.conv2.bias', 'encoder.down_blocks.2.resnets.1.norm1.bias', 'decoder.up_blocks.2.resnets.2.conv2.weight', 'encoder.mid_block.attentions.0.value.bias', 'encoder.mid_block.resnets.0.conv2.weight', 'decoder.up_blocks.0.resnets.1.conv1.bias', 'encoder.down_blocks.3.resnets.0.conv2.weight', 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'decoder.conv_in.bias', 'decoder.mid_block.resnets.1.norm1.bias', 'decoder.up_blocks.2.resnets.2.norm1.weight', 'encoder.down_blocks.3.resnets.1.conv2.weight', 'encoder.mid_block.resnets.1.conv1.bias', 'decoder.up_blocks.2.resnets.0.conv2.bias', 'decoder.up_blocks.3.resnets.0.conv1.bias', 'encoder.down_blocks.1.resnets.1.norm1.bias', 'encoder.down_blocks.2.resnets.0.conv_shortcut.weight', 'decoder.mid_block.attentions.0.key.bias', 'decoder.mid_block.resnets.0.norm1.weight', 'encoder.mid_block.attentions.0.key.weight', 'decoder.mid_block.attentions.0.value.weight', 'encoder.down_blocks.1.resnets.1.conv2.weight', 'encoder.mid_block.attentions.0.value.weight', 'decoder.up_blocks.3.resnets.0.conv2.weight', 'encoder.down_blocks.3.resnets.1.norm2.weight', 'decoder.up_blocks.0.resnets.0.norm1.weight', 'encoder.mid_block.attentions.0.query.bias', 'decoder.up_blocks.0.resnets.2.norm2.bias', 'decoder.up_blocks.2.resnets.1.norm1.bias', 'decoder.up_blocks.2.resnets.1.norm2.bias', 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'encoder.down_blocks.3.resnets.0.norm1.weight', 'decoder.conv_in.weight', 'decoder.mid_block.resnets.0.conv1.weight', 'decoder.mid_block.resnets.1.conv2.bias', 'decoder.up_blocks.0.resnets.2.norm2.weight', 'encoder.down_blocks.1.resnets.0.conv2.weight', 'decoder.up_blocks.3.resnets.0.norm2.bias', 'encoder.down_blocks.0.resnets.1.conv1.weight', 'decoder.mid_block.resnets.1.conv2.weight', 'decoder.mid_block.resnets.1.norm2.bias', 'decoder.up_blocks.1.resnets.1.norm1.bias', 'decoder.up_blocks.0.resnets.0.conv2.weight', 'encoder.down_blocks.0.resnets.0.conv2.bias', 'encoder.down_blocks.3.resnets.1.conv2.bias', 'decoder.up_blocks.2.resnets.0.conv1.bias', 'encoder.down_blocks.1.resnets.1.norm1.weight', 'encoder.down_blocks.2.resnets.0.norm1.bias', 'decoder.up_blocks.1.resnets.2.conv1.weight', 'decoder.up_blocks.0.resnets.1.conv1.weight', 'decoder.up_blocks.0.resnets.2.conv1.weight', 'decoder.up_blocks.3.resnets.1.conv2.weight', 'decoder.up_blocks.3.resnets.2.conv2.weight', 'decoder.up_blocks.3.resnets.2.conv1.bias', 'decoder.up_blocks.2.resnets.0.conv_shortcut.weight', 'decoder.up_blocks.1.resnets.2.norm2.bias', 'decoder.up_blocks.3.resnets.1.conv1.bias', 'encoder.down_blocks.2.resnets.0.norm2.weight', 'encoder.down_blocks.2.resnets.1.conv1.bias', 'decoder.up_blocks.1.resnets.0.conv1.weight', 'encoder.down_blocks.2.resnets.0.conv1.bias', 'decoder.up_blocks.3.resnets.2.conv1.weight', 'decoder.up_blocks.0.resnets.1.conv2.weight', 'decoder.mid_block.attentions.0.proj_attn.weight', 'decoder.mid_block.attentions.0.query.weight', 'encoder.mid_block.resnets.1.norm2.bias', 'encoder.conv_out.bias', 'decoder.mid_block.resnets.0.norm1.bias', 'decoder.mid_block.resnets.0.norm2.weight', 'decoder.up_blocks.3.resnets.1.norm1.weight', 'decoder.up_blocks.3.resnets.0.conv_shortcut.bias', 'encoder.mid_block.resnets.0.norm1.weight', 'decoder.up_blocks.2.resnets.1.norm1.weight', 'encoder.down_blocks.0.resnets.0.norm2.bias', 'decoder.up_blocks.1.resnets.1.norm2.weight', 'decoder.up_blocks.0.resnets.2.norm1.weight', 'encoder.down_blocks.0.resnets.1.norm1.bias', 'encoder.down_blocks.1.resnets.0.norm1.weight', 'encoder.down_blocks.1.resnets.0.conv_shortcut.weight', 'encoder.mid_block.attentions.0.group_norm.weight', 'encoder.down_blocks.0.resnets.0.conv2.weight', 'decoder.up_blocks.0.resnets.0.conv1.weight', 'decoder.conv_out.weight'}]. A potential way to correctly save your model is to use `save_model`. More information at https://huggingface.co/docs/safetensors/torch_shared_tensors '.