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https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-09 06:45:09 +00:00
update sdxl ver in lora metadata from v0-9 to v1-0
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@@ -61,15 +61,15 @@ def svd(args):
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else:
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print(f"loading original SDXL model : {args.model_org}")
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text_encoder_o1, text_encoder_o2, _, unet_o, _, _ = sdxl_model_util.load_models_from_sdxl_checkpoint(
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sdxl_model_util.MODEL_VERSION_SDXL_BASE_V0_9, args.model_org, "cpu"
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sdxl_model_util.MODEL_VERSION_SDXL_BASE_V1_0, args.model_org, "cpu"
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)
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text_encoders_o = [text_encoder_o1, text_encoder_o2]
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print(f"loading original SDXL model : {args.model_tuned}")
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text_encoder_t1, text_encoder_t2, _, unet_t, _, _ = sdxl_model_util.load_models_from_sdxl_checkpoint(
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sdxl_model_util.MODEL_VERSION_SDXL_BASE_V0_9, args.model_tuned, "cpu"
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sdxl_model_util.MODEL_VERSION_SDXL_BASE_V1_0, args.model_tuned, "cpu"
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)
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text_encoders_t = [text_encoder_t1, text_encoder_t2]
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model_version = sdxl_model_util.MODEL_VERSION_SDXL_BASE_V0_9
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model_version = sdxl_model_util.MODEL_VERSION_SDXL_BASE_V1_0
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# create LoRA network to extract weights: Use dim (rank) as alpha
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if args.conv_dim is None:
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@@ -234,7 +234,7 @@ def merge(args):
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unet,
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logit_scale,
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ckpt_info,
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) = sdxl_model_util.load_models_from_sdxl_checkpoint(sdxl_model_util.MODEL_VERSION_SDXL_BASE_V0_9, args.sd_model, "cpu")
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) = sdxl_model_util.load_models_from_sdxl_checkpoint(sdxl_model_util.MODEL_VERSION_SDXL_BASE_V1_0, args.sd_model, "cpu")
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merge_to_sd_model(text_model1, text_model2, unet, args.models, args.ratios, merge_dtype)
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