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README.md
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Model trained with LoRA implementation of Diffusion DPO Read more [here](https://github.com/huggingface/diffusers/tree/main/examples/research_projects/diffusion_dpo)
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Base Model: https://huggingface.co/stabilityai/stable-diffusion-
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## Running with [🧨 diffusers library](https://github.com/huggingface/diffusers)
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variant="fp16",
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)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(
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pipe.scheduler.config,
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)
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pipe.to("cuda");
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seed = 12341234123
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prompt = "professional portrait photo of a girl, photograph, highly detailed face, depth of field, moody light, golden hour, style by Dan Winters, Russell James, Steve McCurry, centered, extremely detailed, Nikon D850, award winning photography"
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negative_prompt = "3d render, cartoon, drawing, art, low light, blur, pixelated, low resolution, black and white"
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num_inference_steps =
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height = 1024
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width = height
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guidance_scale =
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pipe.unload_lora_weights()
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pipe.load_lora_weights(
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# weight_name="pytorch_lora_weights.safetensors",
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adapter_name="sdxl-dpo-lora",
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)
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pipe.set_adapters(["sdxl-dpo-lora"], adapter_weights=[
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generator = torch.Generator().manual_seed(seed)
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with_dpo = pipe(
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prompt=prompt,
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adapter_weights
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Base Model: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
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## Running with [🧨 diffusers library](https://github.com/huggingface/diffusers)
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variant="fp16",
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)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(
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pipe.scheduler.config,
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use_karras_sigmas=True,
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algorithm_type="sde-dpmsolver++"
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)
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pipe.to("cuda");
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seed = 12341234123
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prompt = "professional portrait photo of a girl, photograph, highly detailed face, depth of field, moody light, golden hour, style by Dan Winters, Russell James, Steve McCurry, centered, extremely detailed, Nikon D850, award winning photography"
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negative_prompt = "3d render, cartoon, drawing, art, low light, blur, pixelated, low resolution, black and white"
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num_inference_steps = 40
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height = 1024
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width = height
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guidance_scale = 7.5
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pipe.unload_lora_weights()
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pipe.load_lora_weights(
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# weight_name="pytorch_lora_weights.safetensors",
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adapter_name="sdxl-dpo-lora",
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)
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pipe.set_adapters(["sdxl-dpo-lora"], adapter_weights=[0.9])
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generator = torch.Generator().manual_seed(seed)
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with_dpo = pipe(
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prompt=prompt,
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adapter_weights
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