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README.md
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@@ -49,7 +49,7 @@ from diffusers import StableDiffusionXLPipeline, LCMScheduler
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sd_pipe = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", add_watermarker=False).to('cuda')
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sd_scheduler = LCMScheduler.from_config(sd_pipe.scheduler.config)
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sd_pipe.load_lora_weights(
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```
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Following import the customized OMS pipeline to wrap the backbone and add OMS for sampling. We have uploaded the `.safetensors` to [HuggingFace Hub](https://huggingface.co/h1t/). There are 2 choices for SDXL backbone currently, one is base OMS module with OpenCLIP text encoder [h1t/oms_b_openclip_xl)](https://huggingface.co/h1t/oms_b_openclip_xl) and the other is large OMS module with two text encoder followed by SDXL architecture [h1t/oms_l_mixclip_xl)](https://huggingface.co/h1t/oms_b_mixclip_xl).
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sd_pipe = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", add_watermarker=False).to('cuda')
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sd_scheduler = LCMScheduler.from_config(sd_pipe.scheduler.config)
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sd_pipe.load_lora_weights('latent-consistency/lcm-lora-sdxl', variant="fp16")
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```
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Following import the customized OMS pipeline to wrap the backbone and add OMS for sampling. We have uploaded the `.safetensors` to [HuggingFace Hub](https://huggingface.co/h1t/). There are 2 choices for SDXL backbone currently, one is base OMS module with OpenCLIP text encoder [h1t/oms_b_openclip_xl)](https://huggingface.co/h1t/oms_b_openclip_xl) and the other is large OMS module with two text encoder followed by SDXL architecture [h1t/oms_l_mixclip_xl)](https://huggingface.co/h1t/oms_b_mixclip_xl).
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