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.mv

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+Revision:master,CreatedAt:1765509310

README.md

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+# Z-Image Turbo Acceleration Capability Fix LoRA
+
+## Model Introduction
+
+This model is a LoRA used to fix the acceleration capability of Z-Image Turbo LoRA.
+
+LoRAs trained directly based on Z-Image Turbo will lose their acceleration capability. Images generated under acceleration configuration (steps=8, cfg=1) become blurry, while images generated under non-acceleration configuration (steps=30, cfg=2) remain normal.
+
+## Results
+
+Training Data:
+
+![](assets/training_data.jpg)
+
+Generation Results:
+
+|steps=8, cfg=1|steps=30, cfg=2|steps=8, cfg=1, with our model fix|
+|-|-|-|
+|![](assets/image_base_acc.jpg)|![](assets/image_base_nonacc.jpg)|![](assets/image_with_our_lora.jpg)|
+
+## Inference Code
+
+```python
+from diffsynth.pipelines.z_image import ZImagePipeline, ModelConfig
+import torch
+
+pipe = ZImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="transformer/*.safetensors"),
+        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="text_encoder/*.safetensors"),
+        ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    tokenizer_config=ModelConfig(model_id="Tongyi-MAI/Z-Image-Turbo", origin_file_pattern="tokenizer/"),
+)
+pipe.load_lora(pipe.dit, "path/to/your/lora.safetensors")
+pipe.load_lora(pipe.dit, ModelConfig(model_id="DiffSynth-Studio/Z-Image-Turbo-DistillPatch", origin_file_pattern="model.safetensors"))
+
+image = pipe(prompt="a dog", seed=42, rand_device="cuda")
+image.save("image.jpg")
+```

configuration.json

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+{"aigc_model":true,"framework":"Pytorch","model_file_location":"model.safetensors"}

model.safetensors

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