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from diffsynth import ModelManager, download_models, FluxImagePipeline |
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import torch |
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download_models(["InstantX/FLUX.1-dev-IP-Adapter", "FLUX.1-dev"]) |
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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/IpAdapter/InstantX/FLUX.1-dev-IP-Adapter/ip-adapter.bin", |
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"models/IpAdapter/InstantX/FLUX.1-dev-IP-Adapter/image_encoder", |
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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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]) |
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seed = 42 |
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pipe = FluxImagePipeline.from_model_manager(model_manager) |
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torch.manual_seed(seed) |
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origin_prompt = "a rabbit in a garden, colorful flowers" |
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image = pipe( |
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prompt=origin_prompt, |
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cfg_scale=1.0, embedded_guidance=3.5, |
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height=1280, width=960, num_inference_steps=30 |
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) |
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image.save("style image.jpg") |
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torch.manual_seed(seed) |
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image = pipe( |
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prompt="A piggy", |
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cfg_scale=1.0, embedded_guidance=3.5, |
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height=1280, width=960, num_inference_steps=30, |
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ipadapter_images=[image], ipadapter_scale=0.7 |
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) |
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image.save("A piggy.jpg") |
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