Update app.py

app.py

@@ -1,25 +1,27 @@
+import os 
+
 import gradio as gr
 from transformers import pipeline
 
-classifier = pipeline("zero-shot-classification", model="MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7")
+classifier = pipeline("zero-shot-classification", model=os.getenv('MODEL'))
 
 def classify(text, labels):
     labels = labels.split(',')
     if not text or not labels:
         return []
     result = classifier(text, candidate_labels=labels)
-    return list(zip(result['labels'], result['scores']))
+    return list(zip(result['labels'], map(lambda x: round(x, 4), result['scores'])))
 
 with gr.Blocks() as demo:
-    gr.Markdown("## Zero-Shot Text Classification")
+    gr.Markdown("## Zero-Shot классификация")
     
     with gr.Row():
-        with gr.Column(scale=1):
-            text_input = gr.Textbox(label="Text for classification", placeholder="Enter text here...")
-            labels_input = gr.Textbox(label="Classes (comma separated)", placeholder="Enter classes separated by commas...")
-            button = gr.Button("Classify")
         with gr.Column(scale=2):
-            output = gr.Dataframe(headers=["Class", "Probability"], label="Classification Results")
+            text_input = gr.Textbox(label="Текст для классификации", placeholder="Введите текст...")
+            labels_input = gr.Textbox(label="Классы (через запятую)", placeholder="Опишите классы через запятую...")
+            button = gr.Button("Classify")
+        with gr.Column(scale=1):
+            output = gr.Dataframe(headers=["       Класс       ", "Вероятность"], label="Результаты классификации")
     
     button.click(classify, inputs=[text_input, labels_input], outputs=output)