Update app.py

app.py

@@ -2,8 +2,6 @@
 from os import O_ACCMODE
 import gradio as gr
 from transformers import pipeline
-# from huggingface_hub import HfApi, hf_hub_download
-# from huggingface_hub.repocard import metadata_load
 
 app = gr.Blocks()
 
@@ -13,7 +11,7 @@ model_id_3 = "distilbert-base-uncased-finetuned-sst-2-english"
 model_id_4 = "lordtt13/emo-mobilebert"
 model_id_5 = "juliensimon/reviews-sentiment-analysis"
 
-def parse_output(output_json):  # list of list of dicts
+def parse_output(output_json):  
     list_pred=[]
     for i in range(len(output_json[0])):
         label = output_json[0][i]['label']
@@ -75,11 +73,11 @@ with app:
             btn5 = gr.Button("Predict - Model 5")
 
         with gr.Column():
-            out_1 = gr.Textbox(label="Predictions for Model 1", lines=5)
-            out_2 = gr.Textbox(label="Predictions for Model 2", lines=5)  
-            out_3 = gr.Textbox(label="Predictions for Model 3", lines=5)        
-            out_4 = gr.Textbox(label="Predictions for Model 4", lines=5)     
-            out_5 = gr.Textbox(label="Predictions for Model 5", lines=5)     
+            out_1 = gr.Textbox(label="Predictions for Model 1")
+            out_2 = gr.Textbox(label="Predictions for Model 2")  
+            out_3 = gr.Textbox(label="Predictions for Model 3")        
+            out_4 = gr.Textbox(label="Predictions for Model 4")     
+            out_5 = gr.Textbox(label="Predictions for Model 5")     
 
         btn1.click(fn=get_prediction(model_id_1), inputs=inp_1, outputs=out_1)
         btn2.click(fn=get_prediction(model_id_2), inputs=inp_1, outputs=out_2)