Update app.py

app.py

@@ -13,15 +13,15 @@ torch.backends.cuda.matmul.allow_tf32 = True
 base_model = "black-forest-labs/FLUX.1-dev"
 pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
 
-lora_repo = "kaytoo2022/kaytoo2022-flux"
+lora_repo = "kaytoo2022/jguan_35-flux"
 trigger_word = ""  # Leave trigger_word blank if not used.
-pipe.load_lora_weights(lora_repo, adapter_name='kaytoo')
+pipe.load_lora_weights(lora_repo, adapter_name='jguan')
 
 # ghibsky
 lora_repo_2 = "aleksa-codes/flux-ghibsky-illustration"
 pipe.load_lora_weights(lora_repo_2, adapter_name='lora_2')
 
-pipe.set_adapters(["kaytoo", "lora_2"], adapter_weights=[0.85, 0.0])
+pipe.set_adapters(["jguan", "lora_2"], adapter_weights=[0.85, 0.0])
 
 pipe.to("cuda")
 
@@ -34,7 +34,7 @@ def run_lora(prompt, cfg_scale, steps, randomize_seed, seed, width, height, lora
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device="cuda").manual_seed(seed)
 
-    pipe.set_adapters(["kaytoo", "lora_2"], adapter_weights=[lora_scale, lora_scale_2])
+    pipe.set_adapters(["jguan", "lora_2"], adapter_weights=[lora_scale, lora_scale_2])
 
     # Update progress bar (0% saat mulai)
     progress(0, "Starting image generation...")