#### Model Setting pretrained_model_name_or_path = 'stablediffusionapi/albedobase-xl-20' pretrained_vae_model_name_or_path = 'madebyollin/sdxl-vae-fp16-fix' revision = None byt5_max_length = 512 byt5_mapper_type = 'T5EncoderBlockByT5Mapper' byt5_mapper_config = dict( num_layers=4, sdxl_channels=2048, ) byt5_config = dict( byt5_name='google/byt5-small', special_token=True, color_special_token=True, font_special_token=True, color_ann_path='assets/color_idx.json', font_ann_path='assets/multilingual_10-lang_idx.json', multilingual=True, ) attn_block_to_modify = [ "down_blocks.1.attentions.0.transformer_blocks.0", "down_blocks.1.attentions.0.transformer_blocks.1", "down_blocks.1.attentions.1.transformer_blocks.0", "down_blocks.1.attentions.1.transformer_blocks.1", "down_blocks.2.attentions.0.transformer_blocks.0", "down_blocks.2.attentions.0.transformer_blocks.1", "down_blocks.2.attentions.0.transformer_blocks.2", "down_blocks.2.attentions.0.transformer_blocks.3", "down_blocks.2.attentions.0.transformer_blocks.4", "down_blocks.2.attentions.0.transformer_blocks.5", "down_blocks.2.attentions.0.transformer_blocks.6", "down_blocks.2.attentions.0.transformer_blocks.7", "down_blocks.2.attentions.0.transformer_blocks.8", "down_blocks.2.attentions.0.transformer_blocks.9", "down_blocks.2.attentions.1.transformer_blocks.0", "down_blocks.2.attentions.1.transformer_blocks.1", "down_blocks.2.attentions.1.transformer_blocks.2", "down_blocks.2.attentions.1.transformer_blocks.3", "down_blocks.2.attentions.1.transformer_blocks.4", "down_blocks.2.attentions.1.transformer_blocks.5", "down_blocks.2.attentions.1.transformer_blocks.6", "down_blocks.2.attentions.1.transformer_blocks.7", "down_blocks.2.attentions.1.transformer_blocks.8", "down_blocks.2.attentions.1.transformer_blocks.9", "up_blocks.0.attentions.0.transformer_blocks.0", "up_blocks.0.attentions.0.transformer_blocks.1", "up_blocks.0.attentions.0.transformer_blocks.2", "up_blocks.0.attentions.0.transformer_blocks.3", "up_blocks.0.attentions.0.transformer_blocks.4", "up_blocks.0.attentions.0.transformer_blocks.5", "up_blocks.0.attentions.0.transformer_blocks.6", "up_blocks.0.attentions.0.transformer_blocks.7", "up_blocks.0.attentions.0.transformer_blocks.8", "up_blocks.0.attentions.0.transformer_blocks.9", "up_blocks.0.attentions.1.transformer_blocks.0", "up_blocks.0.attentions.1.transformer_blocks.1", "up_blocks.0.attentions.1.transformer_blocks.2", "up_blocks.0.attentions.1.transformer_blocks.3", "up_blocks.0.attentions.1.transformer_blocks.4", "up_blocks.0.attentions.1.transformer_blocks.5", "up_blocks.0.attentions.1.transformer_blocks.6", "up_blocks.0.attentions.1.transformer_blocks.7", "up_blocks.0.attentions.1.transformer_blocks.8", "up_blocks.0.attentions.1.transformer_blocks.9", "up_blocks.0.attentions.2.transformer_blocks.0", "up_blocks.0.attentions.2.transformer_blocks.1", "up_blocks.0.attentions.2.transformer_blocks.2", "up_blocks.0.attentions.2.transformer_blocks.3", "up_blocks.0.attentions.2.transformer_blocks.4", "up_blocks.0.attentions.2.transformer_blocks.5", "up_blocks.0.attentions.2.transformer_blocks.6", "up_blocks.0.attentions.2.transformer_blocks.7", "up_blocks.0.attentions.2.transformer_blocks.8", "up_blocks.0.attentions.2.transformer_blocks.9", "up_blocks.1.attentions.0.transformer_blocks.0", "up_blocks.1.attentions.0.transformer_blocks.1", "up_blocks.1.attentions.1.transformer_blocks.0", "up_blocks.1.attentions.1.transformer_blocks.1", "up_blocks.1.attentions.2.transformer_blocks.0", "up_blocks.1.attentions.2.transformer_blocks.1", "mid_block.attentions.0.transformer_blocks.0", "mid_block.attentions.0.transformer_blocks.1", "mid_block.attentions.0.transformer_blocks.2", "mid_block.attentions.0.transformer_blocks.3", "mid_block.attentions.0.transformer_blocks.4", "mid_block.attentions.0.transformer_blocks.5", "mid_block.attentions.0.transformer_blocks.6", "mid_block.attentions.0.transformer_blocks.7", "mid_block.attentions.0.transformer_blocks.8", "mid_block.attentions.0.transformer_blocks.9", ] unet_lora_rank = 128 inference_dtype = 'fp16'