Load VAE component

vae = AutoencoderKL.from_pretrained( "madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16 )

Configure the pipeline

pipe = StableDiffusionXLPipeline.from_pretrained( "dataautogpt3/ProteusV0.3", vae=vae, torch_dtype=torch.float16 ) pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config) pipe.to('cuda')

Define prompts and generate image

prompt = "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed" negative_prompt = "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"

image = pipe( prompt, negative_prompt=negative_prompt, width=1024, height=1024, guidance_scale=7, num_inference_steps=20 ).images[0]

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