Update app.py

app.py

@@ -15,12 +15,9 @@ model = SentenceTransformer("all-MiniLM-L6-v2")
 with open("/content/embedding.pkl", "rb") as f:
     Lencode = pickle.load(f)
 
-# Load saved model
-with open("/content/ModelRec.pkl", "rb") as f:
-    lModelRec = pickle.load(f)
 
 def recomm(inputPaper):
-    encodePaper = lModelRec.encode(inputPaper)
+    encodePaper = model.encode(inputPaper)
     cosine_score = util.cos_sim(Lencode, encodePaper)
     top_scores = torch.topk(cosine_score, dim=0, k=4)
     paperList = []