Update app.py

app.py

@@ -10,8 +10,8 @@ import PIL
 base = "stabilityai/stable-diffusion-xl-base-1.0"
 repo = "tianweiy/DMD2"
 checkpoints = {
-    "1-Step" : ["dmd2_sdxl_1step_unet.bin", 1],
-    "4-Step" : ["dmd2_sdxl_4step_unet.bin", 4],
+    "1-Step" : ["dmd2_sdxl_1step_unet_fp16.bin", 1],
+    "4-Step" : ["dmd2_sdxl_4step_unet_fp16.bin", 4],
 }
 loaded = None
 
@@ -37,7 +37,7 @@ def generate_image(prompt, ckpt):
     num_inference_steps = checkpoints[ckpt][1]
 
     if loaded != num_inference_steps:
-        unet.load_state_dict(torch.load(hf_hub_download(repo, checkpoints)), map_location="cuda")
+        unet.load_state_dict(torch.load(hf_hub_download(repo, checkpoint)), map_location="cuda")
         pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", prediction_type="sample" if num_inference_steps==1 else "epsilon")
         loaded = num_inference_steps
         
@@ -51,7 +51,7 @@ def generate_image(prompt, ckpt):
 
 with gr.Blocks(css=CSS) as demo:
     gr.HTML("<h1><center>Adobe DMD2🦖</center></h1>")
-    gr.HTML("<p><center><a href='https://huggingface.co/tianweiy/DMD2'>https://huggingface.co/tianweiy/DMD2</a> text-to-image generation</center></p>")
+    gr.HTML("<p><center><a href='https://huggingface.co/tianweiy/DMD2'>DMD2</a> text-to-image generation</center></p>")
     with gr.Group():
         with gr.Row():
             prompt = gr.Textbox(label='Enter your prompt (English)', scale=8)