Update app.py

app.py

@@ -2,45 +2,19 @@ import gradio as gr
 from gradio import inputs, outputs
 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 translator function
-    def translate_text(text, target_language):
     # ... (the rest of the code)
 
-    # Define the Gradio interface
-    language_options = ["Spanish", "French", "Italian", "Ukrainian"]
-    inputs = [
+# Define the Gradio interface
+language_options = ["Spanish", "French", "Italian", "Ukrainian"]
+inputs = [
     inputs.Textbox(lines=5, label="Enter text to translate:"),
     inputs.Dropdown(choices=language_options, label="Select target language:"),
-    ]
-    outputs = 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()
+]
+outputs = 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()