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https://github.com/kohya-ss/sd-scripts.git
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don't run when not needed
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@@ -626,7 +626,8 @@ def train(args):
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metadata["ss_training_finished_at"] = str(time.time())
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metadata["ss_training_finished_at"] = str(time.time())
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print(f"saving checkpoint: {ckpt_file}")
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print(f"saving checkpoint: {ckpt_file}")
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unwrap_model(network).save_weights(ckpt_file, save_dtype, minimum_metadata if args.no_metadata else metadata)
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unwrap_model(network).save_weights(ckpt_file, save_dtype, minimum_metadata if args.no_metadata else metadata)
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huggingface_util.upload(ckpt_file, args, "/" + ckpt_name)
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if args.huggingface_repo_id is not None:
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huggingface_util.upload(ckpt_file, args, "/" + ckpt_name)
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def remove_old_func(old_epoch_no):
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def remove_old_func(old_epoch_no):
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old_ckpt_name = train_util.EPOCH_FILE_NAME.format(model_name, old_epoch_no) + "." + args.save_model_as
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old_ckpt_name = train_util.EPOCH_FILE_NAME.format(model_name, old_epoch_no) + "." + args.save_model_as
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@@ -666,7 +667,8 @@ def train(args):
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print(f"save trained model to {ckpt_file}")
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print(f"save trained model to {ckpt_file}")
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network.save_weights(ckpt_file, save_dtype, minimum_metadata if args.no_metadata else metadata)
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network.save_weights(ckpt_file, save_dtype, minimum_metadata if args.no_metadata else metadata)
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huggingface_util.upload(ckpt_file, args, "/" + ckpt_name)
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if args.huggingface_repo_id is not None:
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huggingface_util.upload(ckpt_file, args, "/" + ckpt_name)
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print("model saved.")
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print("model saved.")
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