Update app.py

app.py

@@ -41,9 +41,9 @@ def infer(
 
     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.unet, "Bordoglor/Ramzes_sd_v1.5/unet")
-        pipe.load_lora_weights("Bordoglor/Ramzes_sd_v1.5", subfolder="unet")
-        pipe.text_encoder = PeftModel.from_pretrained(pipe.text_encoder, "Bordoglor/Ramzes_sd_v1.5/text_encoder")
+        pipe.unet = PeftModel.from_pretrained(pipe.unet, "Bordoglor/Ramzes_adapter_sd_v1.5", subfolder="unet")
+        #pipe.load_lora_weights("Bordoglor/Ramzes_adapter_sd_v1.5", subfolder="unet")
+        pipe.text_encoder = PeftModel.from_pretrained(pipe.text_encoder, "Bordoglor/Ramzes_adapter_sd_v1.5", subfolder="text_encoder")
     else:     
         pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch_dtype)
     pipe = pipe.to(device)