add lora to model

app.py

@@ -33,8 +33,11 @@ def infer(
     else:
         torch_dtype = torch.float32
     #print(model_id)
-
-    pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
+    if model_id == "CompVis/stable-diffusion-v1-4" and lora == "pepe":
+        lora_id = "seregasmirnov/pepe-lora"
+        pipe = DiffusionPipeline.from_pretrained(model_id, lora_id, torch_dtype=torch_dtype)
+    else:
+        pipe = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
     pipe = pipe.to(device)