Update app.py

app.py

@@ -16,13 +16,13 @@ os.system("pip3 install -U numpy")
 
 
 hf_hub_download(repo_id="fun-research/TiTok", filename="maskgit-vqgan-imagenet-f16-256.bin", local_dir="./")
-hf_hub_download(repo_id="yucornetto/RAR", filename="rar_b.bin", local_dir="./")
+hf_hub_download(repo_id="yucornetto/RAR", filename="rar_xl.bin", local_dir="./")
 
 # @spaces.GPU
 def load_model():
     device = "cuda" if torch.cuda.is_available() else "cpu"
     # load config
-    rar_model_size = "rar_b"
+    rar_model_size = "rar_xl"
     config = demo_util.get_config("configs/training/generator/rar.yaml")
     config.experiment.generator_checkpoint = f"{rar_model_size}.bin"
     config.model.generator.hidden_size = {"rar_b": 768, "rar_l": 1024, "rar_xl": 1280, "rar_xxl": 1408}[rar_model_size]
@@ -67,7 +67,7 @@ def demo_infer(
     return samples
 
 with gr.Blocks() as demo:
-    gr.Markdown("<h1 style='text-align: center'>An Image is Worth 32 Tokens for Reconstruction and Generation</h1>")
+    gr.Markdown("<h1 style='text-align: center'>Randomized Autoregressive Visual Generation (This demo runs with RAR-XL)</h1>")
 
     with gr.Tabs():
         with gr.TabItem('Generate'):