Create app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from gradio.mix import Parallel, Series
+
+from transformers import pipeline
+
+summariser = pipeline("text2text-generation", model="balaramas/mbart-enhiriser")
+
+
+def summarise(inp, direction):
+    if direction == 'en->vi':
+        text = "en: " + inp
+    else:
+        text = "vi: " + inp
+        
+    res = summariser(
+        text,
+        max_length=512,
+        early_stopping=True,
+    )[0]['translation_text'][3:]
+    return res
+
+description = """
+<p>
+<center>
+Multi-domain Summarisation Between English and Hindi
+</center>
+</p>
+"""
+examples = [
+    [" I remember when I first arrived in the United States. Even before the plane landed, the little windows in the airplane revealed snow and ice-covered houses and buildings. As I walked off the plane, cold air crept through the corrugated ramp that led to the airport terminal. Some people inside the airport were wearing big coats and hats, which I had seen on television, but never up close. I felt a little dizzy and needed to sit down, and then my cell phone rang. It was my Aunt Sophia. She was waiting for me outside in the passenger pick-up area, so I walked quickly to the exit, forgetting all about my luggage. When the sliding glass door opened to the outside, there was my aunt–a woman I hadn’t seen in over ten years–wearing a parka and waving her arms frantically in my direction.", "en->hi"]
+]
+iface = gr.Interface(
+    fn=summarise,
+
+    title="🌸English to Hindi Summariser🌸",
+    description=description,
+    article=article,
+    examples=examples,
+    inputs=[
+        gr.inputs.Textbox(lines=5, placeholder="Enter paragraph (maximum 20 lines)", label="Input"),
+        gr.inputs.Radio(
+            choices=[
+                'en->hi'],
+            default='en->hi',
+            label='Direction'),
+    ],
+    outputs="text")
+
+iface.launch(enable_queue=True)