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https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
@@ -213,7 +213,6 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
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if _transformer is not None:
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transformer = _transformer
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elif quant == 'fp8' or quant == 'fp4' or quant == 'nf4' or 'Model' in shared.opts.bnb_quantization:
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print('HERE0')
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_transformer, _text_encoder_2 = load_flux_bnb(file_path, diffusers_load_config)
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if _transformer is not None:
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transformer = _transformer
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@@ -223,7 +222,6 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
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if _transformer is not None:
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transformer = _transformer
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else:
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print('HERE1')
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quant_args = {}
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quant_args = model_quant.create_bnb_config(quant_args)
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if quant_args:
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@@ -232,8 +230,6 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
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quant_args = model_quant.create_ao_config(quant_args)
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if quant_args:
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model_quant.load_torchao(f'Load model: type=Sana quant={quant_args}')
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print('HERE2', diffusers_load_config)
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print('HERE3', quant_args)
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transformer = diffusers.FluxTransformer2DModel.from_single_file(file_path, **diffusers_load_config, **quant_args)
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if transformer is None:
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shared.log.error('Failed to load UNet model')
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