Update README.md
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README.md
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- **Guidance scale:** 3.0 – 5.0
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- **Inference steps:** 28 – 50
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- **Negative prompts:** Strongly recommended for better control
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### Usage Example
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import torch
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from diffusers import ZImagePipeline
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#
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# Use bfloat16 for optimal performance on supported GPUs
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pipe = ZImagePipeline.from_pretrained(
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"Tongyi-MAI/Z-Image",
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torch_dtype=torch.bfloat16,
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)
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pipe.to("cuda")
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#
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prompt = "两名年轻亚裔女性紧密站在一起,背景为朴素的灰色纹理墙面,可能是室内地毯地面。左侧女性留着长卷发,身穿藏青色毛衣,左袖有奶油色褶皱装饰,内搭白色立领衬衫,下身白色裤子;佩戴小巧金色耳钉,双臂交叉于背后。右侧女性留直肩长发,身穿奶油色卫衣,胸前印有“Tunthetables”字样,下方为“New ideas”,搭配白色裤子;佩戴银色小环耳环,双臂交叉于胸前。两人均面带微笑直视镜头。照片,自然光照明,柔和阴影,以藏青、奶油白为主的中性色调,休闲时尚摄影,中等景深,面部和上半身对焦清晰,姿态放松,表情友好,室内环境,地毯地面,纯色背景。"
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negative_prompt = "" #
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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height=1280,
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width=720,
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cfg_normalization=
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num_inference_steps=50,
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guidance_scale=4.0,
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generator=torch.Generator("cuda").manual_seed(42),
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).images[0]
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- **Guidance scale:** 3.0 – 5.0
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- **Inference steps:** 28 – 50
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- **Negative prompts:** Strongly recommended for better control
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- **CFG normalization:** `False` for general stylism, `True` for more realism
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### Usage Example
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import torch
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from diffusers import ZImagePipeline
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# Load the pipeline
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pipe = ZImagePipeline.from_pretrained(
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"Tongyi-MAI/Z-Image",
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torch_dtype=torch.bfloat16,
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)
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pipe.to("cuda")
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# Generate image
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prompt = "两名年轻亚裔女性紧密站在一起,背景为朴素的灰色纹理墙面,可能是室内地毯地面。左侧女性留着长卷发,身穿藏青色毛衣,左袖有奶油色褶皱装饰,内搭白色立领衬衫,下身白色裤子;佩戴小巧金色耳钉,双臂交叉于背后。右侧女性留直肩长发,身穿奶油色卫衣,胸前印有“Tunthetables”字样,下方为“New ideas”,搭配白色裤子;佩戴银色小环耳环,双臂交叉于胸前。两人均面带微笑直视镜头。照片,自然光照明,柔和阴影,以藏青、奶油白为主的中性色调,休闲时尚摄影,中等景深,面部和上半身对焦清晰,姿态放松,表情友好,室内环境,地毯地面,纯色背景。"
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negative_prompt = "" # Optional, but would be powerful when you want to remove some unwanted content
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image = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt,
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height=1280,
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width=720,
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cfg_normalization=True,
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num_inference_steps=50,
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guidance_scale=4.0,
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generator=torch.Generator("cuda").manual_seed(42),
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).images[0]
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