Update app.py

app.py

@@ -37,9 +37,15 @@ def infer(
         torch_dtype = torch.float16
     else:
         torch_dtype = torch.float32
-        
-    pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
-    pipe = pipe.to(device)
+
+    if model == "Ramzes":
+        pipe = StableDiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch_dtype)
+        pipe.unet = PeftModel.from_pretrained(pipe_v5_2.unet, "Bordoglor/Ramzes_adapter_sd_v1.5/unet")
+        pipe.text_encoder = PeftModel.from_pretrained(pipe_v5_2.text_encoder, "Bordoglor/Ramzes_adapter_sd_v1.5/text_encoder")
+        pipe = pipe.to(device)
+    else:     
+        pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
+        pipe = pipe.to(device)
 
     image = pipe(
         prompt=prompt,
@@ -67,7 +73,7 @@ with gr.Blocks(css=css) as demo:
 
         with gr.Row():
             model = gr.Dropdown(
-                choices=["stabilityai/sdxl-turbo", "CompVis/stable-diffusion-v1-4"],
+                choices=["stabilityai/sdxl-turbo", "CompVis/stable-diffusion-v1-4", "Ramzes"],
                 value=model_repo_id,
                 label="Model",
                 info="Choose which diffusion model to use"
@@ -137,7 +143,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=20,  # Replace with defaults that work for your model
+                    value=3,  # Replace with defaults that work for your model
                 )
 
     gr.on(