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28 lines
854 B
Python
28 lines
854 B
Python
from diffsynth import ModelManager, FluxImagePipeline, download_models, QwenPrompt
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import torch
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download_models(["FLUX.1-dev", "QwenPrompt"])
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model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cuda")
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model_manager.load_models([
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"models/FLUX/FLUX.1-dev/text_encoder/model.safetensors",
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"models/FLUX/FLUX.1-dev/text_encoder_2",
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"models/FLUX/FLUX.1-dev/ae.safetensors",
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"models/FLUX/FLUX.1-dev/flux1-dev.safetensors",
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"models/QwenPrompt/qwen2-1.5b-instruct",
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])
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pipe = FluxImagePipeline.from_model_manager(model_manager, prompt_refiner_classes=[QwenPrompt])
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prompt = "鹰"
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negative_prompt = ""
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for seed in range(4):
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torch.manual_seed(seed)
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image = pipe(
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prompt=prompt, negative_prompt=negative_prompt,
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height=1024, width=1024,
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num_inference_steps=30
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)
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image.save(f"{seed}.jpg")
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