Create app.py

app.py

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+import gradio as gr
+from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
+
+# Load the model and tokenizer
+model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
+tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
+
+# Define the language codes supported by the model
+language_codes = {
+    "Arabic": "ar_AR",
+    "Czech": "cs_CZ",
+    "German": "de_DE",
+    "English": "en_XX",
+    "Spanish": "es_XX",
+    "Estonian": "et_EE",
+    "Finnish": "fi_FI",
+    "French": "fr_XX",
+    "Gujarati": "gu_IN",
+    "Hindi": "hi_IN",
+    "Italian": "it_IT",
+    "Japanese": "ja_XX",
+    "Kazakh": "kk_KZ",
+    "Korean": "ko_KR",
+    "Lithuanian": "lt_LT",
+    "Latvian": "lv_LV",
+    "Burmese": "my_MM",
+    "Nepali": "ne_NP",
+    "Dutch": "nl_XX",
+    "Romanian": "ro_RO",
+    "Russian": "ru_RU",
+    "Sinhala": "si_LK",
+    "Turkish": "tr_TR",
+    "Vietnamese": "vi_VN",
+    "Chinese": "zh_CN",
+}
+
+def translate(text, src_lang, tgt_lang):
+    # Set the source language
+    tokenizer.src_lang = language_codes[src_lang]
+    
+    # Tokenize the input text
+    encoded = tokenizer(text, return_tensors="pt")
+    
+    # Generate translation
+    generated_tokens = model.generate(
+        **encoded,
+        forced_bos_token_id=tokenizer.lang_code_to_id[language_codes[tgt_lang]]
+    )
+    
+    # Decode the generated tokens
+    translation = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
+    
+    return translation
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Textbox(label="Input Text"),
+        gr.Dropdown(choices=list(language_codes.keys()), label="Source Language"),
+        gr.Dropdown(choices=list(language_codes.keys()), label="Target Language"),
+    ],
+    outputs=gr.Textbox(label="Translated Text"),
+    title="Multilingual Translation with MBart",
+    description="Translate text between multiple languages using the MBart model.",
+)
+
+# Launch the interface
+iface.launch()