fixing multiple model inference

app.py

@@ -67,6 +67,12 @@ class Demo:
         self.device = 'cuda'
         self.weight_dtype = torch.bfloat16
         model_id = "stabilityai/sdxl-turbo"
+        model_id = 'stabilityai/stable-diffusion-xl-base-1.0'
+        pipe = StableDiffusionXLPipeline.from_pretrained(model_id, torch_dtype=self.weight_dtype).to(self.device)
+        pipe = None
+        del pipe
+        torch.cuda.empty_cache()
+        
         self.current_model = 'SDXL Turbo'
         euler_anc = EulerAncestralDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
         self.pipe = StableDiffusionXLPipeline.from_pretrained(model_id, scheduler=euler_anc, torch_dtype=self.weight_dtype).to(self.device)