Create main.py

main.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define the translator function
+def translate_text(text, target_language):
+    model_name = {
+        "Spanish": "Helsinki-NLP/opus-mt-en-es",
+        "French": "Helsinki-NLP/opus-mt-en-fr",
+        "Italian": "Helsinki-NLP/opus-mt-en-it",
+        "Ukrainian": "Helsinki-NLP/opus-mt-en-uk",
+    }
+
+    tokenizer = MarianTokenizer.from_pretrained(model_name[target_language])
+    model = MarianMTModel.from_pretrained(model_name[target_language])
+
+    # Tokenize the input text
+    input_tokens = tokenizer(text, return_tensors="pt")
+
+    # Generate translated tokens
+    translated_tokens = model.generate(**input_tokens)
+
+    # Decode the translated tokens
+    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+
+    return translated_text
+
+# Define the Gradio interface
+language_options = ["Spanish", "French", "Italian", "Ukrainian"]
+inputs = [
+    gr.inputs.Textbox(lines=5, label="Enter text to translate:"),
+    gr.inputs.Dropdown(choices=language_options, label="Select target language:"),
+]
+outputs = gr.outputs.Textbox(label="Translated text:")
+
+iface = gr.Interface(fn=translate_text, inputs=inputs, outputs=outputs, title="Language Translator")
+
+# Launch the Hugging Face Spaces app
+iface.launch()