Update app.py

app.py

@@ -74,6 +74,7 @@ def process_entity(batch, model, device):
 
     # Convert tensor to list of token IDs, and decode them into a readable sentence
     pseudo_sentence_decoded = bert_tokenizer.decode(pseudo_sentence[0].tolist(), skip_special_tokens=False)
+    st.write("Pseudo Sentence: ", pseudo_sentence_decoded)
 
     with torch.no_grad():
         outputs = spaBERT_model(#input_ids=input_ids,
@@ -98,12 +99,6 @@ for batch in (data_loader):
     spaBERT_embedding, input_ids, pseudo_sentence = process_entity(batch, spaBERT_model, device)
     spaBERT_embeddings.append(spaBERT_embedding)
     pseudo_sentences.append(pseudo_sentence)
-
-# Print all the pseudo sentences
-print("Pseudo Sentences:")
-for idx, sentence in enumerate(pseudo_sentences):
-    print(f"{idx + 1}: {sentence}")
-
     
 embedding_cache = {}