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custom diffusion
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@@ -156,7 +156,7 @@ pipe = pipeline(
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modifier_token='<new1>',
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model_revision=args.model_revision)
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output = pipe({'text': args.prompt})
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output = pipe({'text': args.instance_prompt})
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# visualize the result on ipynb and save it
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output
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cv2.imwrite('./custom_result.png', output['output_imgs'][0])
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@@ -6,7 +6,7 @@ PYTHONPATH=. torchrun examples/pytorch/stable_diffusion/custom/finetune_stable_d
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--work_dir './tmp/custom_diffusion' \
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--class_data_dir './tmp/class_data' \
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--train_dataset_name 'buptwq/lora-stable-diffusion-finetune-dog' \
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--max_epochs 1 \
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--max_epochs 250 \
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--modifier_token "<new1>" \
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--num_class_images=200 \
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--save_ckpt_strategy 'by_epoch' \
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