Update app.py

app.py

@@ -1,27 +1,32 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
 
-# Define the translation pipeline
-translator = pipeline("translation", model="facebook/mbart-large-50-many-to-many-mmt")
+# Load the model and tokenizer
+model_name = "facebook/mbart-large-50-many-to-many-mmt"
+model = M2M100ForConditionalGeneration.from_pretrained(model_name)
+tokenizer = M2M100Tokenizer.from_pretrained(model_name)
 
 # Define the Gradio interface
 def translate_text(text, target_language):
-    translated_text = translator(text, target_language)[0]['translation_text']
+    # Encode the input text and decode the translated text
+    input_ids = tokenizer.encode(text, return_tensors="pt", padding=True, truncation=True)
+    translated_ids = model.generate(input_ids, decoder_start_token_id=tokenizer.lang_code_to_id(target_language))
+    translated_text = tokenizer.decode(translated_ids[0], skip_special_tokens=True)
     return translated_text
 
 iface = gr.Interface(
     fn=translate_text,
     inputs=[
-        gr.components.Textbox(label="Input Text"),
-        gr.components.Dropdown(
+        gr.inputs.Textbox(label="Input Text"),
+        gr.inputs.Dropdown(
             label="Target Language",
-            choices=["es", "fr", "de", "it"],  # Add more languages as needed
+            choices=["es", "fr", "de", "it", "en"],  # Add more languages as needed
         ),
     ],
-    outputs=gr.components.Textbox(label="Translated Text"),
+    outputs=gr.outputs.Textbox(label="Translated Text"),
     live=True,
     title="Multilingual Translation Tool",
-    description="Translate text into multiple languages using facebook/mbart-large-50-many-to-many-mmt model.",
+    description=f"Translate text into multiple languages using {model_name} model.",
 )
 
 # Start the Gradio interface