Update app.py

app.py

@@ -5,10 +5,10 @@ from transformers import DistilBertTokenizer, DistilBertModel
 class SimilarityPredictor:
     def __init__(self):
         self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-        self.model = DistilBertModel.from_pretrained('patent_similarity_model').to(self.device)
-        self.tokenizer = DistilBertTokenizer.from_pretrained('patent_similarity_model')
+        # Use the base model instead of custom model
+        self.model = DistilBertModel.from_pretrained('distilbert-base-uncased').to(self.device)
+        self.tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-uncased')
         self.head = torch.nn.Sequential(torch.nn.Linear(768, 1), torch.nn.Sigmoid()).to(self.device)
-        self.head.load_state_dict(torch.load('patent_similarity_model/head.pt', map_location=self.device))
         
     def predict(self, anchor, target):
         self.model.eval()
@@ -27,25 +27,18 @@ class SimilarityPredictor:
 
 predictor = SimilarityPredictor()
 
-# Örnek seçenekler
 example_pairs = [
     ["mobile phone", "cellphone"],
     ["artificial intelligence", "machine learning"],
     ["electric vehicle", "battery powered car"],
     ["wireless communication", "radio transmission"],
-    ["solar panel", "photovoltaic cell"],
-    ["computer processor", "CPU"],
-    ["digital storage", "memory device"],
-    ["touch screen", "interactive display"],
-    ["biometric authentication", "fingerprint recognition"],
-    ["cloud computing", "remote server processing"]
+    ["solar panel", "photovoltaic cell"]
 ]
 
 def predict_similarity(anchor, target):
     score = predictor.predict(anchor, target)
     return round(score, 3)
 
-# Create Gradio interface with examples
 iface = gr.Interface(
     fn=predict_similarity,
     inputs=[
@@ -54,19 +47,9 @@ iface = gr.Interface(
     ],
     outputs=gr.Number(label="Similarity Score (0-1)"),
     title="Patent Phrase Similarity Checker",
-    description="""Compare the similarity between two patent phrases.
-    
-    Score guide:
-    - 1.0: Very close match (exact or near-exact)
-    - 0.75: Close synonyms
-    - 0.5: Related terms
-    - 0.25: Somewhat related
-    - 0.0: Unrelated
-    
-    Try the examples below or enter your own phrases!""",
+    description="Compare the similarity between two patent phrases (0: Different, 1: Identical)",
     examples=example_pairs,
-    theme="huggingface",
-    css="footer {display: none !important;}"
+    theme="huggingface"
 )
 
 iface.launch()