Update app.py

app.py

@@ -11,7 +11,6 @@ import os
 
 from diffusers import DiffusionPipeline
 from transformers import pipeline
-# from peft import PeftModel
 from PIL import Image
 
 # Pre-Initialize
@@ -43,6 +42,8 @@ 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)
+repo_default.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
+repo_default.set_adapters(["base"], adapter_weights=[0.7])
 
 # repo_large = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, add_watermarker=False, revision="refs/pr/1")
 # repo_large.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
@@ -50,9 +51,9 @@ repo_default = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", d
 
 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,
+    # "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_neo,
 }
 
@@ -100,9 +101,6 @@ def generate(input=DEFAULT_INPUT, filter_input="", negative_input=DEFAULT_NEGATI
     else:
         steps_set = 25
         guidance_set = 7
-        
-        repo.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
-        repo.set_adapters(["base"], adapter_weights=[0.7])
 
     if not steps:
         steps = steps_set