Update app.py

app.py

@@ -2,14 +2,32 @@ import gradio as gr
 from transformers import pipeline
 translation_pipeline_german = pipeline('translation_en_to_de')
 translation_pipeline_hindi = pipeline('translation_en_to_de')
+def hindi_translate(text_):
+    from transformers import MarianMTModel, MarianTokenizer
+    # Load the English to Hindi translation model and tokenizer
+    model_name = "Helsinki-NLP/opus-mt-en-hi"
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    # English text to be translated
+    english_text = text_
+    # Tokenize the input text
+    inputs = tokenizer.encode(english_text, return_tensors="pt")
+    # Perform translation
+    translation = model.generate(inputs)
+    # Decode the translation
+    hindi_translation = tokenizer.decode(translation[0], skip_special_tokens=True)
+    return hindi_translation
+    
 # results = translation_pipeline('I love ice cream')
 # results[0]['translation_text']
 def translate_transformers(English,Language_To_Translate):
     if "German" in Language_To_Translate:
         results = translation_pipeline_german(English)
+        return results[0]['translation_text']
     elif "Hindi" in  Language_To_Translate:
-        results = translation_pipeline_hindi(English)
-    return results[0]['translation_text']
+        results = hindi_translate(English)
+        return results
+    
 
 interface = gr.Interface(fn=translate_transformers, 
                          inputs=[gr.inputs.Textbox(lines=2, placeholder='Text to translate'),