Update app.py

app.py

@@ -9,12 +9,15 @@ import numpy as np
 from PIL import Image
 import spaces
 import torch
-from diffusers import StableDiffusionXLPipeline, KDPM2AncestralDiscreteScheduler, AutoencoderKL
-
+from diffusers import (
+    StableDiffusionXLPipeline, 
+    KDPM2AncestralDiscreteScheduler,
+    AutoencoderKL
+)
 DESCRIPTION = """
-# Proteus ```V0.3```
+# Mobius
 
-Model by [dataautogpt3](https://huggingface.co/dataautogpt3)
+Model by [Corcel.io](https://huggingface.co/Corcelio/mobius)
 
 Demo by [ehristoforu](https://huggingface.co/ehristoforu)
 """
@@ -29,27 +32,19 @@ ENABLE_CPU_OFFLOAD = 0
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 
-if torch.cuda.is_available():
-    pipe = StableDiffusionXLPipeline.from_pretrained(
-        "dataautogpt3/ProteusV0.3",
-        use_safetensors=False,
-    )
-    if ENABLE_CPU_OFFLOAD:
-        pipe.enable_model_cpu_offload()
-    else:
-        vae = AutoencoderKL.from_pretrained(
-            "madebyollin/sdxl-vae-fp16-fix", 
-            torch_dtype=torch.float16
-        )
-        pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-        pipe.to(device)    
-        print("Loaded on Device!")
-    pipe.load_lora_weights("stabilityai/stable-diffusion-xl-base-1.0", weight_name="sd_xl_offset_example-lora_1.0.safetensors")
-    pipe.fuse_lora(lora_scale=0.1)
-    if USE_TORCH_COMPILE:
-        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
-        print("Model Compiled!")
+vae = AutoencoderKL.from_pretrained(
+    "madebyollin/sdxl-vae-fp16-fix", 
+    torch_dtype=torch.float16
+)
 
+# Configure the pipeline
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "Corcelio/mobius", 
+    vae=vae,
+    torch_dtype=torch.float16
+)
+pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+pipe.to('cuda')
 
 def save_image(img):
     unique_name = str(uuid.uuid4()) + ".png"
@@ -87,7 +82,7 @@ def generate(
         width=width,
         height=height,
         guidance_scale=guidance_scale,
-        num_inference_steps=35,
+        num_inference_steps=25,
         num_images_per_prompt=1,
         output_type="pil",
     ).images
@@ -115,7 +110,7 @@ footer {
     visibility: hidden
 }
 '''
-with gr.Blocks(title="Proteus V0.3", css=css) as demo:
+with gr.Blocks(title="Mobius", css=css) as demo:
     gr.Markdown(DESCRIPTION)
     gr.DuplicateButton(
         value="Duplicate Space for private use",
@@ -157,14 +152,14 @@ with gr.Blocks(title="Proteus V0.3", css=css) as demo:
                 minimum=512,
                 maximum=1536,
                 step=8,
-                value=768,
+                value=1024,
             )
             height = gr.Slider(
                 label="Height",
                 minimum=512,
                 maximum=1536,
                 step=8,
-                value=768,
+                value=1024,
             )
         with gr.Row():
             guidance_scale = gr.Slider(