Update app.py

app.py

@@ -41,20 +41,17 @@ footer {
 
 repo_nsfw_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection")
 
-# repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
-# repo_default.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="default_base")
-# repo_default.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="pixel_base")
-# repo_default.load_lora_weights("nerijs/pixel-art-xl", adapter_name="pixel_base_2")
-
-repo_large = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, use_safetensors=True, add_watermarker=False)
-# repo_large.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
+repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
+repo_default.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="default_base")
+repo_default.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="pixel_base")
+repo_default.load_lora_weights("nerijs/pixel-art-xl", adapter_name="pixel_base_2")
 
 repo_customs = {
-    # "Default": repo_default,
-    # "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
-    # "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
-    # "Pixel": repo_default,
-    "Large": repo_large,
+    "Default": repo_default,
+    "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
+    "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
+    "Pixel": repo_default,
+    "Large": DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, use_safetensors=True, add_watermarker=False),
 }
 
 # Functions
@@ -93,7 +90,7 @@ def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATI
         guidance_set = 1.5
         repo.set_adapters(["pixel_base", "pixel_base_2"], adapter_weights=[1, 1])
     elif model == "Large":
-        steps_set = 25
+        steps_set = 10
         guidance_set = 3.5
     else:
         steps_set = 25