Update app.py

app.py

@@ -33,20 +33,6 @@ pipe = pipe.to(device)
 
 
 
-dtype = torch.float16
-pipe2 = FluxWithCFGPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-schnell", torch_dtype=dtype
-)
-pipe2.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype)
-pipe2.to("cuda")
-pipe2.load_lora_weights('hugovntr/flux-schnell-realism', weight_name='schnell-realism_v2.3.safetensors', adapter_name="better")
-pipe2.set_adapters(["better"], adapter_weights=[1.0])
-pipe2.fuse_lora(adapter_name=["better"], lora_scale=1.0)
-pipe2.unload_lora_weights()
-
-torch.cuda.empty_cache()
-
-
 
 
 def adjust_to_nearest_multiple(value, divisor=8):
@@ -110,8 +96,8 @@ def infer(
 
     generator = torch.Generator().manual_seed(seed)
 
-    if num_inference_steps<=10:
-        image = pipe(
+    
+    image = pipe(
             prompt=prompt,
             negative_prompt=negative_prompt,
             guidance_scale=guidance_scale,
@@ -120,14 +106,7 @@ def infer(
             height=height,
             generator=generator,
         ).images[0]
-    else:
-        img = pipe2.generate_images( 
-            prompt=prompt,
-            width=width,
-            height=height,
-            num_inference_steps=num_inference_steps,
-            generator=generator
-        )
+    
 
     return image, seed