Create app.py

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+from transformers import pipeline
+
+pipe = pipeline("zero-shot-classification",model='MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7')
+
+with gr.Blocks() as demo:
+    txt = gr.Textbox('Введите текст', label='Текст для классификации', interactive=True)
+    with gr.Row():
+        labels = gr.DataFrame(
+            headers=['Labels'], 
+            row_count=(2, 'static'), 
+            col_count=(1, 'fixed'),
+            datatype='str', 
+            interactive=True, 
+            scale=4,
+        )
+        submit = gr.Button('Обработать', scale=1)
+    with gr.Group():
+        with gr.Row():
+            checkbox = gr.Checkbox(
+                label='Множественная положительная классификация', 
+                interactive=True, 
+                info='',
+            )
+            dropdown = gr.Dropdown(
+                label='Number of Labels to predict', 
+                multiselect=False, 
+                value=1, 
+                choices=list(range(1,6),),
+                interactive=False,
+            )
+    result = gr.Label(
+        label='Результат классификации', 
+        visible=False,
+    )
+
+    def activate_dropdown(ob):
+        if not ob:
+            return gr.Dropdown(
+                interactive=ob, 
+                value=1,
+            )
+        return gr.Dropdown(interactive=ob)
+
+    def submit_btn(text, df, label_no):
+        output = pipe(
+            text, 
+            list(df['Labels']), 
+            multi_label=True,
+        )
+        return gr.Label(
+            visible=True, 
+            num_top_classes=int(label_no),
+            value={i: j for i, j in zip(output['labels'], output['scores'])}
+        )
+
+    checkbox.change(activate_dropdown, inputs=[checkbox], outputs=[dropdown])
+    submit.click(submit_btn, inputs=[txt, labels, dropdown], outputs=[result])
+demo.launch()