Update app.py

app.py

@@ -1,5 +1,6 @@
 
 from transformers import BertTokenizer, BertForSequenceClassification
+import torch
 import gradio as gr
 
 model_path = 'elliealbertson/identifying_pregnancy_clinical_notes'
@@ -35,8 +36,8 @@ def predict(text):
         return error_message
 
 with gr.Blocks() as interface:
-    gr.Markdown("<h1 align='center'>Identifying Pregnancy in Clinical Notes</h1>")
-    gr.Markdown("<p align='center'>Use this app to classify a clinical note as discussing or not discussing the patient's pregnancy.</p>")
+    gr.HTML("<div style='text-align:center;'><div><h1>Identifying Pregnancy in Clinical Notes</h1></div>")
+    gr.HTML("<p align='center'>Use this app to classify a clinical note as discussing or not discussing the patient's pregnancy.</p>")
     with gr.Row():
         with gr.Column():
             inputs = gr.Textbox(label='Input a clinical note here:', lines=4)
@@ -45,6 +46,6 @@ with gr.Blocks() as interface:
         with gr.Column():
             outputs=gr.Textbox(label="Does the note discuss the patient's pregnancy?", lines=4)
             button.click(fn=predict, inputs=inputs, outputs=outputs, queue=False)
-    gr.Markdown("<p align='center'>Model fine-tuned from <a href='https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT' target='_blank'> Bio+ClinicalBERT </a>.</p>")
+    gr.HTML("<p align='center'>Model fine-tuned from <a href='https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT' target='_blank'> Bio+ClinicalBERT </a>.</p>")
 
 interface.launch()