Upload app.py

app.py

@@ -55,6 +55,7 @@ def perform_asde_inference(text, dataset, model_id):
         tokenized_text = tokenizer_english(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
         output = double_english_generator.generate(tokenized_text.input_ids,max_length=512)
         model_generated = tokenizer_english.decode(output[0], skip_special_tokens=True)
+
     '''
     elif model_id == "PyABSA_Hospital_Multilingual_allenai/tk-instruct-base-def-pos_FinedTuned_Model":
         tokenized_text = tokenizer_multilingual(bos_instruction + text + delim_instruct + eos_instruct, return_tensors="pt")
@@ -73,7 +74,7 @@ def perform_asde_inference(text, dataset, model_id):
     if not text:
         true_doubles = pd.DataFrame(list(map(list, zip(ast.literal_eval(true_aspect), ast.literal_eval(true_sentiment)))),columns=['Aspect','Sentiment'])
     else:
-        true_doubles = pd.DataFrame()
+        true_doubles = pd.DataFrame([["",""]],columns=['Aspect','Sentiment'])
 
     return pred_doubles, true_doubles, text, model_generated