Update app.py

app.py

@@ -15,7 +15,7 @@ negative_preds = grouped_predictions.get_group(0)
 predictions_df['Prediction'] = predictions_df['Prediction'].map({0: 'Negative', 1: 'Neutral', 2: 'Positive'})
 
 # Load training data set
-dataset = load_dataset("eengel7/sentiment_analysis_training", split='train')
+dataset = load_dataset("torileatherman/sentiment_analysis_training", split='train')
 training_df = pd.DataFrame(dataset)
 random_sample = {}
 
@@ -63,7 +63,7 @@ def thanks(sentiment):
     # Upload training data set
     ds = Dataset.from_pandas(training_df)
     try: 
-        ds.push_to_hub("eengel7/sentiment_analysis_training")
+        ds.push_to_hub("torileatherman/sentiment_analysis_training")
     except StopIteration:
         pass
 
@@ -96,15 +96,6 @@ with gr.Blocks() as manual_label_demo:
     submit_btn =  gr.Button('Submit your sentiment!')
     submit_btn.click(fn=thanks, inputs=drop_down_label, outputs=gr.Textbox())
 
-manual_label_demo1 = gr.Interface(
-    fn=thanks,
-    title="Manually Label a News Article",
-    inputs=[gr.Textbox(label = "Paste in URL of news article here."),
-            gr.Dropdown(["Positive","Negative","Neutral"], label="Select the sentiment of the news article.")],
-    outputs = gr.Textbox(label="Output"),
-    description = description2
-)
-
 
 demo = gr.TabbedInterface([suggestion_demo, manual_label_demo], ["Get recommended news articles", "Help improve our model"])