| import gradio as gr | |
| from transformers import MarianMTModel, MarianTokenizer | |
| model_name = "Helsinki-NLP/opus-mt-en-te" | |
| tokenizer = MarianTokenizer.from_pretrained(model_name) | |
| model = MarianMTModel.from_pretrained(model_name) | |
| def translate(text): | |
| if not text.strip(): | |
| return "Please enter English text." | |
| inputs = tokenizer(text, return_tensors="pt", padding=True) | |
| translated = model.generate(**inputs) | |
| output = tokenizer.decode(translated[0], skip_special_tokens=True) | |
| return output | |
| demo = gr.Interface(fn=translate, | |
| inputs="text", | |
| outputs="text", | |
| title="English to Telugu Translator", | |
| description="Enter English text to get Telugu translation.") | |
| demo.launch() |