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license: mit |
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## How to run |
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```python |
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import torch |
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from diffusers import AutoPipelineForText2Image |
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from diffusers.pipelines.wuerstchen import WuerstchenPrior |
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prior_model = WuerstchenPrior.from_pretrained("warp-diffusion/wuerstchen-prior", torch_dtype=torch.float16) |
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pipe = AutoPipelineForText2Image.from_pretrained("warp-diffusion/wuerstchen", prior_prior=prior_model, torch_dtype=torch.float16).to("cuda") |
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prompt = [ |
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"An old destroyed car standing on a cliff in norway, cinematic photography", |
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"Western movie, closeup cinematic photography", |
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"Pink nike shoe commercial, closeup cinematic photography", |
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"Croatia, closeup cinematic photography", |
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"South Tyrol mountains at sunset, closeup cinematic photography", |
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] |
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images = pipe(prompt, guidance_scale=8.0, width=1024, height=1024).images |
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``` |
