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18 lines
925 B
Python
18 lines
925 B
Python
from diffsynth.pipelines.stable_diffusion import StableDiffusionPipeline, ModelConfig
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import torch
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pipe = StableDiffusionPipeline.from_pretrained(
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torch_dtype=torch.float32,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="unet/diffusion_pytorch_model.safetensors"),
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ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="AI-ModelScope/stable-diffusion-v1-5", origin_file_pattern="tokenizer/"),
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)
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prompt = "dog, white and brown dog, sitting on wall, under pink flowers"
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image = pipe(prompt=prompt, seed=42, rand_device="cuda", num_inference_steps=50, cfg_scale=7.5)
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image.save("image.jpg")
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