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on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -85,7 +85,7 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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def load_and_prepare_model():
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#vaeRV = AutoencoderKL.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='vae', safety_checker=None, use_safetensors=True, token=True)
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vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", safety_checker=None, use_safetensors=False, low_cpu_mem_usage=False, torch_dtype=torch.float32, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
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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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#sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", token=True) #, beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True, token=True)
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@@ -97,7 +97,7 @@ def load_and_prepare_model():
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add_watermarker=False,
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#text_encoder=None,
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#text_encoder_2=None,
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)
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#pipe.vae = vaeXL #.to(torch.bfloat16)
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#pipe.scheduler = sched
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@@ -111,9 +111,8 @@ def load_and_prepare_model():
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#pipe.unet.to(memory_format=torch.channels_last)
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#pipe.enable_vae_tiling()
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pipe.to(device=device, dtype=torch.bfloat16)
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pipe.unet.set_attn_processor(AttnProcessor2_0())
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pipe.vae = vaeXL #.to('cpu') #.to(torch.bfloat16)
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pipe.vae.set_default_attn_processor()
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return pipe
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def load_and_prepare_model():
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#vaeRV = AutoencoderKL.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='vae', safety_checker=None, use_safetensors=True, token=True)
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vaeXL = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae", device_map='cpu', safety_checker=None, use_safetensors=False, low_cpu_mem_usage=False, torch_dtype=torch.float32, token=True) #.to(device).to(torch.bfloat16) #.to(device=device, dtype=torch.bfloat16)
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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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#sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear", token=True) #, beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True, token=True)
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add_watermarker=False,
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#text_encoder=None,
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#text_encoder_2=None,
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vae=None,
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)
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#pipe.vae = vaeXL #.to(torch.bfloat16)
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#pipe.scheduler = sched
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#pipe.unet.to(memory_format=torch.channels_last)
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#pipe.enable_vae_tiling()
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pipe.to(device=device, dtype=torch.bfloat16)
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pipe.vae = vaeXL #.to('cpu') #.to(torch.bfloat16)
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pipe.unet.set_attn_processor(AttnProcessor2_0())
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pipe.vae.set_default_attn_processor()
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return pipe
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