Update README.md
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README.md
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@@ -52,10 +52,8 @@ from schedulers.lcm_single_step_scheduler import LCMSingleStepScheduler
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from module.ip_adapter.utils import load_adapter_to_pipe
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from pipelines.sdxl_instantir import InstantIRPipeline
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# prepare models under ./
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-
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previewer_lora_path = f'./models'
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instantir_path = f'./models/aggregator.pt'
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# load pretrained models
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pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16)
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@@ -63,17 +61,17 @@ pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1
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# load adapter
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load_adapter_to_pipe(
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pipe,
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image_encoder_or_path = 'facebook/dinov2-large',
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)
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# load previewer lora
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pipe.prepare_previewers(
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pipe.scheduler = DDPMScheduler.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', subfolder="scheduler")
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lcm_scheduler = LCMSingleStepScheduler.from_config(pipe.scheduler.config)
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# load aggregator weights
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pretrained_state_dict = torch.load(instantir_path)
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pipe.aggregator.load_state_dict(pretrained_state_dict)
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# send to GPU and fp16
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from module.ip_adapter.utils import load_adapter_to_pipe
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from pipelines.sdxl_instantir import InstantIRPipeline
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# prepare models under ./models
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instantir_path = f'./models'
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# load pretrained models
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pipe = InstantIRPipeline.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16)
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# load adapter
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load_adapter_to_pipe(
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pipe,
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f"{instantir_path}/adapter.pt",
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image_encoder_or_path = 'facebook/dinov2-large',
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)
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# load previewer lora
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pipe.prepare_previewers(instantir_path)
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pipe.scheduler = DDPMScheduler.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', subfolder="scheduler")
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lcm_scheduler = LCMSingleStepScheduler.from_config(pipe.scheduler.config)
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# load aggregator weights
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pretrained_state_dict = torch.load(f"{instantir_path}/aggregator.pt")
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pipe.aggregator.load_state_dict(pretrained_state_dict)
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# send to GPU and fp16
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