Update app.py

app.py

@@ -7,6 +7,7 @@ import torch
 import json
 import random
 import copy
+import gc
 
 lora_list = hf_hub_download(repo_id="multimodalart/LoraTheExplorer", filename="sdxl_loras.json", repo_type="space")
 
@@ -45,21 +46,25 @@ css = '''
 '''
 
 #@spaces.GPU
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
+original_pipe = copy.deepcopy(pipe)
+
 def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
-  pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16) 
-  pipe.to(torch_dtype=torch.float16)
-  pipe.to("cuda")
+  pipe = copy.deepcopy(original_pipe)
+  pipe.to(device)  
   print("Loading LoRAs")
   pipe.load_lora_weights(shuffled_items[0]['saved_name'])
   pipe.fuse_lora(lora_1_scale)
   pipe.load_lora_weights(shuffled_items[1]['saved_name'])
   pipe.fuse_lora(lora_2_scale)
   
-  
   if negative_prompt == "":
     negative_prompt = False
-  print("Running inference")
-  image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=25, guidance_scale=7).images[0]
+      
+  image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=25).images[0]
+  del pipe
+  gc.collect()
+  torch.cuda.empty_cache()
   return image
 
 def get_description(item):