Create new file

app.py

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+import gradio as gr
+import re
+import os
+from transformers import pipeline
+
+AUTH_TOKEN = os.environ["AUTH_TOKEN"]
+
+classifier = pipeline('text-classification',
+                      model="djsull/kobigbird-hate-multi-label_short",
+                      use_auth_token=AUTH_TOKEN,
+                      return_all_scores=True,
+                      function_to_apply='sigmoid',
+                      )
+
+def predict(text):
+    query = text
+    cleanr = re.compile('<.*?>')
+    query = re.sub(cleanr, '', query)
+    query = ' '.join(re.sub('[^가-힣a-zA-Z0-9 ]', ' ', query).split())
+
+    result = classifier(query)[0]
+
+    res = []
+    for i in range(len(result)):
+        if result[i]['score'] > 0.1:
+            res.append(result[i]['label'])
+
+    res = ', '.join(res)
+  
+    return res
+
+gr.Interface(
+    predict,
+    inputs=gr.inputs.Textbox(label="Type anything"),
+    outputs=gr.outputs.Textbox(label="labels"),
+    title="curse classification",
+).launch()