Update app.py

app.py

@@ -6,17 +6,20 @@ import gradio as gr
 import numpy as np
 import torch
 from PIL import Image
-from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler
+from diffusers import StableDiffusionXLImg2ImgPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler
 from huggingface_hub import hf_hub_download, InferenceClient
 
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-pipe = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V4.0", torch_dtype=torch.float16, vae=vae)
+pipe = StableDiffusionXLPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, vae=vae)
+pipe.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
+pipe.set_adapters("lora")
 pipe.to("cuda")
 
-refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
+refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
 refiner.to("cuda")
 
-pipe_fast = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V3.0_Turbo", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
+pipe_fast = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V4.0_Lightning", torch_dtype=torch.float16)
+pipe_fast.scheduler = EulerAncestralDiscreteScheduler(pipe_fast.scheduler.config)
 pipe_fast.to("cuda")
 
 help_text = """