Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Load model and tokenizer
+model_name = "VietAI/envit5-translation"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+# Translation function
+def translate(text):
+    input_ids = tokenizer(text, return_tensors="pt", padding=True).input_ids
+    output_ids = model.generate(input_ids, max_length=512)
+    return tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
+
+# Gradio interface
+demo = gr.Interface(
+    fn=translate,
+    inputs="text",
+    outputs="text",
+    title="Vietnamese-English Translation",
+    description="Translate text between English and Vietnamese using the VietAI envit5 model."
+)
+
+# Launch the Gradio app
+demo.launch(debug=True)