--- library_name: diffusers pipeline_tag: text-to-image inference: true base_model: stabilityai/stable-diffusion-xl-base-1.0 --- # DPO LoRA Stable Diffusion XL Model trained with LoRA implementation of Diffusion DPO Read more [here](https://github.com/huggingface/diffusers/tree/main/examples/research_projects/diffusion_dpo) Base Model: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0 ## Running with [🧨 diffusers library](https://github.com/huggingface/diffusers) ```python import torch from diffusers import AutoPipelineForText2Image, DPMSolverMultistepScheduler from diffusers.utils import make_image_grid pipe = AutoPipelineForText2Image.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16", ) pipe.scheduler = DPMSolverMultistepScheduler.from_config( pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++" ) pipe.to("cuda"); seed = 12341234123 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" negative_prompt = "3d render, cartoon, drawing, art, low light, blur, pixelated, low resolution, black and white" num_inference_steps = 40 height = 1024 width = height guidance_scale = 7.5 pipe.unload_lora_weights() pipe.load_lora_weights( "radames/sdxl-DPO-LoRA", adapter_name="sdxl-dpo-lora", ) pipe.set_adapters(["sdxl-dpo-lora"], adapter_weights=[0.9]) generator = torch.Generator().manual_seed(seed) with_dpo = pipe( prompt=prompt, guidance_scale=guidance_scale, negative_prompt=negative_prompt, num_inference_steps=num_inference_steps, width=width, height=height, generator=generator, ).images[0] with_dpo ``` # Adaptor Weights effect adapter_weights ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6064e095abd8d3692e3e2ed6/f69suGIl9Ysnmi52ahol8.jpeg)