Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+import torch
+
+model_checkpoint = "japanese-denim/mbart-50-finetuned-naga-to-eng"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
+tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+
+def translate(text):
+    translation_pipeline = pipeline("translation",
+                                    model=model,
+                                    tokenizer = tokenizer,
+                                    src_lang='ng_XX',
+                                    tgt_lang='en_XX')
+
+    result = translation_pipeline(text)
+    return result[0]['translation_text']
+    
+
+
+gr.Interface(
+    translate,
+    [
+        gr.components.Textbox(label="input", placeholder = "Enter Nagamese sentence here")
+    ],
+    ["text"],
+).launch()