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import subprocess |
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subprocess.run(["accelerate", "launch", "--mixed_precision=fp16", "train_text_to_image_lora.py", |
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"--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5", |
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"--dataset_name=pcuenq/oxford-pets", |
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"--dataloader_num_workers=8", |
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"--resolution=512", "--center_crop", "--random_flip", |
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"--train_batch_size=1", |
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"--gradient_accumulation_steps=4", |
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"--max_train_steps=5000", |
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"--learning_rate=1e-04", |
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"--max_grad_norm=1", |
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"--lr_scheduler=cosine", "--lr_warmup_steps=0", |
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"--output_dir=/home/htelvis92/182/", |
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"--push_to_hub", |
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"--hub_model_id=pets", |
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"--checkpointing_steps=500", |
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"--validation_prompt=Totoro", |
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"--seed=1337", |
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"--caption_column=label"]) |
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