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--- |
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language: |
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- en |
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library_name: diffusers |
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pipeline_tag: text-to-image |
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--- |
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# You Only Sample Once (YOSO) |
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This algorithm was proposed in You Only Sample Once: Taming One-Step Text-To-Image Synthesis by Self-Cooperative Diffusion GANs. |
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This model is fine-tuning from [ |
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PixArt-XL-2-512x512](https://huggingface.co/PixArt-alpha/PixArt-XL-2-512x512), enabling one-step inference to perform text-to-image generation. |
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We wanna highlight that the YOSO-PixArt was originally trained on 512 resolution. However, we found that we can construct a YOSO that enables generating samples with 1024 resolution by merging with [ |
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PixArt-XL-2-1024-MS](https://huggingface.co/PixArt-alpha/PixArt-XL-2-1024-MS |
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) (Eq(15) in the paper) as follows: |
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 |
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The impressive performance indicates the robust generalization ability of our YOSO. |
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## usage |
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```python |
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import torch |
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from diffusers import PixArtAlphaPipeline, LCMScheduler, Transformer2DModel, DPMSolverMultistepScheduler |
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transformer = Transformer2DModel.from_pretrained( |
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"Yihong666/yoso_pixart1024", torch_dtype=torch.float16).to('cuda') |
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pipe = PixArtAlphaPipeline.from_pretrained("PixArt-alpha/PixArt-XL-2-512x512", |
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transformer=transformer, |
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torch_dtype=torch.float16, use_safetensors=True) |
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pipe = pipe.to('cuda') |
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) |
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pipe.scheduler.config.prediction_type = "v_prediction" |
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generator = torch.manual_seed(318) |
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imgs = pipe(prompt="Pirate ship trapped in a cosmic maelstrom nebula, rendered in cosmic beach whirlpool engine, volumetric lighting, spectacular, ambient lights, light pollution, cinematic atmosphere, art nouveau style, illustration art artwork by SenseiJaye, intricate detail.", |
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num_inference_steps=1, |
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num_images_per_prompt = 1, |
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generator = generator, |
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guidance_scale=1., |
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)[0] |
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imgs[0] |
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``` |
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