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DESCRIPTION.md

@@ -0,0 +1 @@
+This simple demo takes advantage of Gradio's HighlightedText, JSON and HTML outputs to create a clear NER segmentation.

README.md

@@ -1,7 +1,7 @@
 
 ---
 title: text_analysis 
-emoji: 🤗
+emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio

app.py

@@ -1,16 +1,11 @@
-# URL: https://huggingface.co/spaces/gradio/text_analysis
-# DESCRIPTION: This simple demo takes advantage of Gradio's HighlightedText, JSON and HTML outputs to create a clear NER segmentation.
-# imports
 import gradio as gr
 import os
 os.system('python -m spacy download en_core_web_sm')
 import spacy
 from spacy import displacy
 
-# load the model
 nlp = spacy.load("en_core_web_sm")
 
-# define the core function
 def text_analysis(text):
     doc = nlp(text)
     html = displacy.render(doc, style="dep", page=True)
@@ -30,7 +25,6 @@ def text_analysis(text):
 
     return pos_tokens, pos_count, html
 
-# define the interface, with a textbox input, and three outputs: HighlightedText, JSON, and HTML
 demo = gr.Interface(
     text_analysis,
     gr.Textbox(placeholder="Enter sentence here..."),
@@ -41,5 +35,4 @@ demo = gr.Interface(
     ],
 )
 
-# launch
 demo.launch()