Update app.py

app.py

@@ -5,14 +5,25 @@ from langdetect import detect, DetectorFactory, detect_langs
 import fasttext
 from transformers import pipeline
 
-models = {'en': 'Narsil/deberta-large-mnli-zero-cls'} #Uzbek
+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
 
 
-hypothesis_templates = {'en': 'This example is {}.'} # Uzbek
+hypothesis_templates = {'en': 'This example is {}.', # English
+                        'ru': 'Этот пример {}.', # Russian
+                        'uz': 'Бу мисол {}.'} # Uzbek
                        
                         
 classifiers = {'en': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['en'],
-                              model=models['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'])
+              }
 
 fasttext_model = fasttext.load_model(hf_hub_download("julien-c/fasttext-language-id", "lid.176.bin"))
 
@@ -23,8 +34,17 @@ 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_text1, example_labels1],
+        [example_text2, example_labels2],
+        [example_text3, example_labels3]
         ]
 
     return examples
@@ -86,8 +106,8 @@ def sequence_to_classify(sequence, labels):
     return clean_output
 
 iface = gr.Interface(
-    title="En Multi-label Zero-shot Classification",
-    description="Supported languages are: English",
+    title="En-Ru-Uz Multi-label Zero-shot Classification",
+    description="Supported languages are: English, Russian and Uzbek",
     fn=sequence_to_classify,
     inputs=[gr.inputs.Textbox(lines=10,
         label="Please enter the text you would like to classify...",