update

app.py

@@ -21,7 +21,7 @@ pipe = FluxPipeline.from_pretrained(bfl_repo, transformer=None, torch_dtype=dtyp
 pipe.transformer = transformer
 pipe.scheduler.config.use_dynamic_shifting = False
 pipe.scheduler.config.time_shift = 10
-pipe.enable_model_cpu_offload()
+# pipe.enable_model_cpu_offload()
 pipe = pipe.to(device)
 
 pipe.load_lora_weights(
@@ -41,7 +41,7 @@ pipe.load_lora_weights(
 )
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
-USE_ZERO_GPU = False
+USE_ZERO_GPU = True
 
 
 # @spaces.GPU #[uncomment to use ZeroGPU]
@@ -57,9 +57,9 @@ def infer(
 ):
     print("Using model:", model)
     if model == "2k":
-        pipe.set_adapter("2k")
+        pipe.set_adapters("2k")
     elif model == "4k":
-        pipe.set_adapter(f"4k_{flux_model}")
+        pipe.set_adapters(f"4k_{flux_model}")
 
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
@@ -106,7 +106,7 @@ css = """
 """
 
 with gr.Blocks(css=css) as demo:
-    gr.Markdown("# UREA")
+    gr.Markdown("# URAE: ")
     with gr.Row(elem_id="maincontainer"):
         with gr.Column(elem_id="col1"):
             gr.Markdown("### Prompt:")