Update app.py

app.py

@@ -1,15 +1,10 @@
 import gradio as gr
 import os
 import torch
-import spacy
-from spacy import displacy
-
-nlp = spacy.load("en_core_web_sm")
 
 # Load model directly
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-
 def get_hatespeech_score(text):
     tokenizer = AutoTokenizer.from_pretrained("unhcr/hatespeech-detection")
     model = AutoModelForSequenceClassification.from_pretrained("unhcr/hatespeech-detection")
@@ -51,17 +46,12 @@ def text_analysis(text):
             </html>
             '''.format("Alpha", label_1, "Gamma", "Theta")
 
-    doc = nlp(text)
-    pos_tokens = []
-    for token in doc:
-        pos_tokens.extend([(token.text, token.pos_), (" ", None)])
-
-    return pos_tokens, html
+    return html
 
 demo = gr.Interface(
     text_analysis,
     gr.Textbox(placeholder="Enter sentence here..."),
-    ["highlight", "html"],
+    ["html"],
     examples=[
         ["What a beautiful morning for a walk!"],
         ["It was the best of times, it was the worst of times."],