Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = "my_awesome_opus_books_model"
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512).input_ids
+    outputs = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
+    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated_text
+
+# Create a Gradio interface
+interface = gr.Interface(fn=translate, 
+                         inputs=gr.Textbox(lines=2, placeholder="Enter English text to translate..."), 
+                         outputs=gr.Textbox(), 
+                         title="English to French Translation",
+                         description="Translate English text to French using a fine-tuned model, start your sentence with translate English to French:")
+
+# Launch the interface
+interface.launch()