Update app.py

app.py

@@ -3,7 +3,8 @@ from transformers import pipeline
 
 
 # Load the summarization & translation model pipeline
-tran_sum_pipe = pipeline("translation", model='utrobinmv/t5_summary_en_ru_zh_base_2048')
+#tran_sum_pipe = pipeline("translation", model='utrobinmv/t5_summary_en_ru_zh_base_2048')
+trans_pipe = pipeline("translation", model='liam168/trans-opus-mt-zh-en')
 sentiment_pipeline = pipeline("text-classification", model='Howosn/Sentiment_Model',return_all_scores=True)
 #tokenizer = AutoTokenizer.from_pretrained('Howosn/Sentiment_Model', use_fast=False)
 
@@ -17,9 +18,9 @@ text = st.text_area("Enter the text", "")
 # Perform analysis result when the user clicks the "Analyse" button
 if st.button("Analyse"):
     # Perform text classification on the input text
-    trans_sum = tran_sum_pipe(text)[0]
-    results = sentiment_pipeline(trans_sum)[0]
-
+    trans = tran_pipe(text)[0]
+    results = sentiment_pipeline(trans)[0]
+    
     # Display the classification result
     max_score = float('-inf')
     max_label = ''