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from diffusers import StableDiffusionPipeline |
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import torch |
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from diffusers import DDIMScheduler |
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model_path = "./new_model" |
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prompt = "a cute girl, blue eyes, brown hair" |
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torch.manual_seed(123123123) |
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pipe = StableDiffusionPipeline.from_pretrained( |
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model_path, |
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torch_dtype=torch.float16, |
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scheduler=DDIMScheduler( |
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beta_start=0.00085, |
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beta_end=0.012, |
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beta_schedule="scaled_linear", |
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clip_sample=False, |
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set_alpha_to_one=True, |
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), |
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safety_checker=None |
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) |
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pipe = pipe.to("cuda") |
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images = pipe(prompt, width=512, height=512, num_inference_steps=30, num_images_per_prompt=3).images |
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for i, image in enumerate(images): |
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image.save(f"test-{i}.png") |
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