u

app.py

@@ -324,9 +324,10 @@ def encode_keywords_to_avg(keywords, model, tokenizer, device):
 
 def encode_keywords_to_list(keywords, model, tokenizer, device):
     embeddings = []
+    model.to(device)  
     for keyword in tqdm(keywords):
         inputs = tokenizer(keyword, return_tensors='pt', padding=True, truncation=True, max_length=512)
-        inputs.to(device)
+        inputs = {key: value.to(device) for key, value in inputs.items()}  
         with torch.no_grad():
             outputs = model(**inputs)
         embeddings.append(outputs.last_hidden_state.mean(dim=1).squeeze().tolist())