Implemented pruning

app.py

@@ -12,6 +12,7 @@ from tqdm import tqdm
 import speech_recognition as sr
 from gtts import gTTS
 import tempfile
+import torch.nn.utils.prune as prune
 
 # Configure logging
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
@@ -27,12 +28,10 @@ class ImageSearchSystem:
         self.model = CLIPModel.from_pretrained("openai/clip-vit-base-patch16").to(self.device)
 
           # Prune the model
-        pruned_model = self.model.prune(
-            pruning_method="l1_unstructured",
-            num_heads_to_prune=10,
-            num_layers_to_prune=2,
+        parameters_to_prune = (
+            (self.model.visual.encoder.layers, 'weight'),
         )
-        self.model = pruned_model
+        prune.l1_unstructured(parameters_to_prune, amount=0.2)
         
         # Initialize dataset
         self.image_paths = []