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29 lines
1.4 KiB
Python
29 lines
1.4 KiB
Python
from diffsynth.pipelines.stable_diffusion_xl import StableDiffusionXLPipeline, ModelConfig
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from diffsynth.core import load_state_dict
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import torch
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pipe = StableDiffusionXLPipeline.from_pretrained(
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torch_dtype=torch.float32,
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model_configs=[
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ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="text_encoder_2/model.safetensors"),
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ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="unet/diffusion_pytorch_model.safetensors"),
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ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="tokenizer/"),
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tokenizer_2_config=ModelConfig(model_id="stabilityai/stable-diffusion-xl-base-1.0", origin_file_pattern="tokenizer_2/"),
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)
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state_dict = load_state_dict("./models/train/stable-diffusion-xl-base-1.0_full/epoch-1.safetensors", torch_dtype=torch.float32)
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pipe.unet.load_state_dict(state_dict)
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image = pipe(
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prompt="a dog",
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negative_prompt="",
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cfg_scale=7.0,
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height=1024,
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width=1024,
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seed=42,
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num_inference_steps=50,
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)
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image.save("image_stable-diffusion-xl-base-1.0_full.jpg")
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