Update app.py

app.py

@@ -74,14 +74,20 @@ interface_words = gr.Interface(
 # )
 # interface_model_L.load("models/DReAMy-lib/xlm-roberta-large-DreamBank-emotion-presence")
 
-pipe_S = pipeline("text-classification", model="DReAMy-lib/bert-base-cased-DreamBank-emotion-presence")
+pipe_S = pipeline(
+    "text-classification",
+    model="DReAMy-lib/bert-base-cased-DreamBank-emotion-presence",
+    max_length=300,
+    return_all_scores=True,
+    truncation="do_not_truncate",
+)
 def predict(text):
     t = pipe_S(text)
     return t
 interface_model_S =  gr.Interface(
         fn=predict,
         inputs='text',
-        outputs=gr.Label,
+        outputs==gr.Label(),
         title="SA Base English-Only",
         description=description_S,
         examples = ["I was followed by the blue monster but was not scared. I was calm and relaxed."],