test scheduler

app.py

@@ -6,17 +6,20 @@ import gradio as gr
 import numpy as np
 import torch
 from PIL import Image
-from diffusers import StableDiffusionXLImg2ImgPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL, EulerAncestralDiscreteScheduler
+from diffusers import StableDiffusionXLImg2ImgPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL, DPMSolverMultistepScheduler
 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.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
+pipe.set_adapters("lora")
+pipe.to("cuda")
 
 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_V4.0_Lightning", torch_dtype=torch.float16, vae=vae)
-pipe_fast.load_lora_weights("KingNish/Better-Image-XL-Lora", weight_name="example-03.safetensors", adapter_name="lora")
-pipe_fast.set_adapters("lora")
+pipe_fast = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V4.0_Lightning", torch_dtype=torch.float16, vae=vae, custom_pipeline="lpw_stable_diffusion_xl", use_safetensors=True)
+pipe_fast.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++")
 pipe_fast.to("cuda")
 
 help_text = """
@@ -183,6 +186,11 @@ examples=[
             None,
             "Beautiful Eiffel Tower at Night",
         ],
+        [
+            "Image Generation",
+            None,
+            "Beautiful Eiffel Tower at Night",
+        ],
     ]
 
 with gr.Blocks(css=css) as demo:
@@ -207,7 +215,7 @@ with gr.Blocks(css=css) as demo:
             negative_prompt = gr.Text(
                     label="Negative prompt",
                     max_lines=1,
-                    value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
+                    value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, ugly, disgusting, blurry, amputation,(face asymmetry, eyes asymmetry, deformed eyes, open mouth)",
                     visible=True)
         with gr.Row():
             width =  gr.Slider( label="Width", minimum=256, maximum=2048, step=64, value=1024)
@@ -220,9 +228,7 @@ with gr.Blocks(css=css) as demo:
                     show_label=False,
                     interactive=True,
                 )
-            seed = gr.Number(value=1371, step=1, label="Seed", interactive=True)
-
-
+            seed = gr.Number(value=2404, step=1, label="Seed", interactive=True)
 
     gr.Examples(
         examples=examples,
@@ -259,4 +265,4 @@ with gr.Blocks(css=css) as demo:
             outputs=[seed, input_image],
         )
 
-demo.queue(max_size=99999).launch()
+demo.queue(max_size=50).launch()