Update app.py

app.py

@@ -17,22 +17,19 @@ transformer = FluxTransformer2DModel.from_pretrained(
 
 
 # Build pipeline
-
-def load_models(model_name):
-    controlnet = FluxControlNetModel.from_pretrained(f"alimama-creative/{model_name}", torch_dtype=torch.bfloat16)
-    pipe = FluxControlNetInpaintingPipeline.from_pretrained(
-        "black-forest-labs/FLUX.1-dev",
-        controlnet=controlnet,
-        transformer=transformer,
-        torch_dtype=torch.bfloat16
-    ).to("cuda")
-    pipe.transformer.to(torch.bfloat16)
-    pipe.controlnet.to(torch.bfloat16)
-    return pipe
+controlnet = FluxControlNetModel.from_pretrained("alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Beta", torch_dtype=torch.bfloat16)
+pipe = FluxControlNetInpaintingPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    controlnet=controlnet,
+    transformer=transformer,
+    torch_dtype=torch.bfloat16
+).to("cuda")
+pipe.transformer.to(torch.bfloat16)
+pipe.controlnet.to(torch.bfloat16)
 
 
 MARKDOWN = """
-# FLUX.1-dev-Inpainting-Model-GPU 🔥
+# FLUX.1-dev-Inpainting-Model-Beta-GPU 🔥
 Model by alimama-creative
 """
 
@@ -40,7 +37,6 @@ Model by alimama-creative
 def process(input_image_editor,
             prompt,
             negative_prompt,
-            model_name,
             controlnet_conditioning_scale,
             guidance_scale,
             seed,
@@ -51,8 +47,6 @@ def process(input_image_editor,
     mask = input_image_editor['layers'][0]
     size = (768, 768)
     image_or = image.copy()
-    pipe = load_models(model_name)
-    pipe =  pipe.to("cuda")
     
     image = image.convert("RGB").resize(size)
     mask = mask.convert("RGB").resize(size)
@@ -87,7 +81,6 @@ with gr.Blocks() as demo:
 
             prompt = gr.Textbox(lines=2, placeholder="Enter prompt here...")
             negative_prompt = gr.Textbox(lines=2, placeholder="Enter negative_prompt here...")
-            model_name = gr.Dropdown(choices=["FLUX.1-dev-Controlnet-Inpainting-Beta","FLUX.1-dev-Controlnet-Inpainting-Alpha"], label="Select Model Inpainting", value="FLUX.1-dev-Controlnet-Inpainting-Beta")
             controlnet_conditioning_scale = gr.Slider(minimum=0, step=0.01, maximum=1, value=0.9, label="controlnet_conditioning_scale")
             guidance_scale = gr.Slider(minimum=1, step=0.5, maximum=10, value=3.5, label="Image to generate")
             seed  = gr.Slider(minimum=0, step=1, maximum=10000000, value=124, label="Seed Value")
@@ -109,7 +102,6 @@ with gr.Blocks() as demo:
             input_image_editor_component,
             prompt,
             negative_prompt,
-            model_name,
             controlnet_conditioning_scale,
             guidance_scale,
             seed,