Update app.py

app.py

@@ -43,18 +43,18 @@ footer {
 
 repo_nsfw_classifier = pipeline("image-classification", model="Falconsai/nsfw_image_detection")
 
-repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False).to(DEVICE)
+repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
 
-repo_neo = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", device=DEVICE, torch_dtype=torch.bfloat16, use_safetensors=False, add_watermarker=False, revision="refs/pr/1").to(DEVICE)
-repo_neo.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
-repo_neo.set_adapters(["base"], adapter_weights=[0.7])
+repo_large = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", device=DEVICE, torch_dtype=torch.bfloat16, add_watermarker=False, revision="refs/pr/1")
+# repo_large.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
+# repo_large.set_adapters(["base"], adapter_weights=[0.7])
 
 repo_customs = {
     "Default": repo_default,
-    "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False).to(DEVICE),
-    "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False).to(DEVICE),
+    "Realistic": DiffusionPipeline.from_pretrained("ehristoforu/Visionix-alpha", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
+    "Anime": DiffusionPipeline.from_pretrained("cagliostrolab/animagine-xl-3.1", device=DEVICE, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False),
     "Pixel": repo_default,
-    "Neo": repo_neo,
+    "Large": repo_neo,
 }
 
 # Functions
@@ -95,9 +95,9 @@ def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATI
         repo.load_lora_weights("artificialguybr/PixelArtRedmond", adapter_name="base")
         repo.load_lora_weights("nerijs/pixel-art-xl", adapter_name="base2")
         repo.set_adapters(["base", "base2"], adapter_weights=[1, 1])
-    elif model == "Neo":
-        steps_set = 4
-        guidance_set = 0
+    elif model == "Large":
+        steps_set = 25
+        guidance_set = 3.5
     else:
         steps_set = 25
         guidance_set = 7