add examples

app.py

@@ -5,7 +5,6 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 import torch
 
-
 title = "Community Tab Language Detection & Translation"
 description = """
 When comments are created in the community tab, detect the language of the content.
@@ -23,8 +22,6 @@ headers = {"Authorization": f"Bearer {ACCESS_TOKEN}"}
 model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
 tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
 device = 0 if torch.cuda.is_available() else -1
-LANGS = ["ace_Arab", "eng_Latn", "fra_Latn", "spa_Latn"]
-
 
 language_code_map = {
     "English": "eng_Latn",
@@ -62,12 +59,18 @@ def query(text, src_lang, tgt_lang):
     return [lang_id, translation]
 
 
+examples = [
+    ["Hello, world", "English", "French"],
+    ["Hasta la vista", "Spanish", "German"],
+    ["동경에 휴가를 간다", "Korean", "Japanese"],
+]
+
 gr.Interface(
     query,
     [
         gr.Textbox(lines=2),
-        gr.Radio(["English", "French", "Korean"], value="English", label="Source Language"),
-        gr.Radio(["Spanish", "German", "Japanese"], value="Spanish", label="Target Language")
+        gr.Radio(["English", "Spanish", "Korean"], value="English", label="Source Language"),
+        gr.Radio(["French", "German", "Japanese"], value="French", label="Target Language")
         # gr.Radio(["English", "French", "Korean"]),
         # gr.Radio(["Spanish", "German", "French"]),
     ],
@@ -76,5 +79,6 @@ gr.Interface(
         gr.Textbox(lines=3, label="Translation")
     ],
     title=title,
-    description=description
+    description=description,
+    examples=examples
 ).launch()