Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load the model and tokenizer
+model_name = 'Helsinki-NLP/opus-mt-en-hi'  # Model for English to Hindi
+model = MarianMTModel.from_pretrained(model_name)
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+
+# Function to translate English to Hindi
+def translate_to_hindi(text):
+    # Tokenize input text
+    tokens = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+    # Perform translation
+    translated_tokens = model.generate(**tokens)
+    # Decode the translation
+    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+    return translated_text
+
+# Gradio interface
+iface = gr.Interface(fn=translate_to_hindi, inputs="text", outputs="text", 
+                     title="English to Hindi Translator", 
+                     description="Enter English text and get the Hindi translation.")
+
+# Launch the interface
+iface.launch()