Update app.py

app.py

@@ -5,25 +5,14 @@ from langdetect import detect, DetectorFactory, detect_langs
 import fasttext
 from transformers import pipeline
 
-models = {'en': 'Narsil/deberta-large-mnli-zero-cls', # English
-          'ru': 'DeepPavlov/xlm-roberta-large-en-ru-mnli', # Russian
-          'uz': 'coppercitylabs/uzbek-news-category-classifier'
-          } #Uzbek
+models = {'en': 'Narsil/deberta-large-mnli-zero-cls'} #Uzbek
 
 
-hypothesis_templates = {'en': 'This example is {}.', # English
-                        'ru': 'Этот пример {}.', # Russian
-                        'uz': 'Бу мисол {}.'} # Uzbek
+hypothesis_templates = {'en': 'This example is {}.'} # Uzbek
                        
                         
 classifiers = {'en': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['en'],
-                              model=models['en']),
-              
-               'ru': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['ru'],
-                              model=models['ru']),
-                'uz': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['uz'],
-                              model=models['uz'])
-              }
+                              model=models['en'])}
 
 fasttext_model = fasttext.load_model(hf_hub_download("julien-c/fasttext-language-id", "lid.176.bin"))
 
@@ -34,17 +23,8 @@ def prep_examples():
     example_labels1 = "business,health related,politics,climate change"
 
     
-    example_text2 = "Том был невероятно рад встрече со своим другом, ученным из Китая, который занимается искусственным интелектом."
-    example_labels2 = "наука,политика"
-
-    example_text3 = "Алишер Навоий ўзбек классик шоири, буюк ижодкор ва ватанпарвар инсон бўлган."
-    example_labels3 = "шеърият,спорт, санъат"
-
-    
     examples = [
-        [example_text1, example_labels1],
-        [example_text2, example_labels2],
-        [example_text3, example_labels3]
+        [example_text1, example_labels1]
         ]
 
     return examples
@@ -106,8 +86,8 @@ def sequence_to_classify(sequence, labels):
     return clean_output
 
 iface = gr.Interface(
-    title="En-Ru-Uz Multi-label Zero-shot Classification",
-    description="Supported languages are: English, Russian and Uzbek",
+    title="En Multi-label Zero-shot Classification",
+    description="Supported languages are: English",
     fn=sequence_to_classify,
     inputs=[gr.inputs.Textbox(lines=10,
         label="Please enter the text you would like to classify...",