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Update app.py
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app.py
CHANGED
@@ -114,8 +114,8 @@ def load_and_prepare_model():
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#sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler',beta_schedule="scaled_linear", steps_offset=1,timestep_spacing="trailing"))
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#sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler', steps_offset=1,timestep_spacing="trailing")
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#sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)
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sched = DPMSolverSDEScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler')
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#pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
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#pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
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pipe = StableDiffusionXLPipeline.from_pretrained(
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@@ -179,12 +179,8 @@ def load_and_prepare_model():
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#pipe.unet=pipeX.unet
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#pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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#pipe.scheduler=EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
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pipe.vae.set_default_attn_processor()
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pipe.to(device)
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pipe.to(torch.bfloat16)
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# pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/Fantasy_World_XL.safetensors", adapter_name="fantasy")
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pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", adapter_name="skin")
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#pipe.unet.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="unet")
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#pipe.text_encoder.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="text_encoder")
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@@ -192,6 +188,10 @@ def load_and_prepare_model():
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#pipe.set_adapters(["skin", "photo", "fantasy"], adapter_weights=[0.75, 0.25, 0.5])
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pipe.set_adapters(["skin"], adapter_weights=[0.5]) #pipe.unet.set_default_attn_processor()
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print(f'Pipeline: ')
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#print(f'_optional_components: {pipe._optional_components}')
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#print(f'watermark: {pipe.watermark}')
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#sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler',beta_schedule="scaled_linear", steps_offset=1,timestep_spacing="trailing"))
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#sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler', steps_offset=1,timestep_spacing="trailing")
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#sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)
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sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
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#sched = DPMSolverSDEScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler')
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#pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
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#pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
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pipe = StableDiffusionXLPipeline.from_pretrained(
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#pipe.unet=pipeX.unet
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#pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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#pipe.scheduler=EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
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# pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/Fantasy_World_XL.safetensors", adapter_name="fantasy")
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pipe.load_lora_weights("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", adapter_name="skin", low_cpu_mem_usage=False)
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#pipe.unet.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="unet")
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#pipe.text_encoder.load_lora_adapter("ford442/sdxl-vae-bf16", weight_name="LoRA/skin_texture_style_v4.safetensors", prefix="text_encoder")
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#pipe.set_adapters(["skin", "photo", "fantasy"], adapter_weights=[0.75, 0.25, 0.5])
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pipe.set_adapters(["skin"], adapter_weights=[0.5]) #pipe.unet.set_default_attn_processor()
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pipe.vae.set_default_attn_processor()
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pipe.to(device)
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pipe.to(torch.bfloat16)
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print(f'Pipeline: ')
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#print(f'_optional_components: {pipe._optional_components}')
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#print(f'watermark: {pipe.watermark}')
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