Create app.py

app.py

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+## import gradio
+import gradio as gr
+
+## install the transformer pipeline
+from transformers import pipeline
+from transformers import AutoModelWithLMHead,AutoTokenizer
+
+mode_name = 'liam168/trans-opus-mt-en-zh'
+model = AutoModelWithLMHead.from_pretrained(mode_name)
+tokenizer = AutoTokenizer.from_pretrained(mode_name)
+
+pipe_ch = pipeline("translation_en_to_zh", model=model, tokenizer=tokenizer)
+
+def translate_ch(text):
+    return pipe_ch(text)[0]["translation_text"]
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            english = gr.Textbox(label="English text")
+            translate_btn = gr.Button(value="Translate")
+        with gr.Column():
+            chinese = gr.Textbox(label="Chinese Text")
+            
+    translate_btn.click(translate_ch, inputs=english, outputs=chinese, api_name="translate-to-chinese")
+    examples = gr.Examples(examples=["I like to study Data Science and Machine Learning.", "Helen is a good swimmer."],
+                           inputs=[english])
+
+demo.launch()