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| # KINYARWANDA TO ENGLISH | |
| import gradio as gr | |
| from transformers import MarianMTModel, MarianTokenizer | |
| # Suppose you found a model 'Helsinki-NLP/opus-mt-rw-en' that translates from Kinyarwanda to English | |
| model_name = 'Helsinki-NLP/opus-mt-rw-en' | |
| tokenizer = MarianTokenizer.from_pretrained(model_name) | |
| model = MarianMTModel.from_pretrained(model_name) | |
| # Function to translate text from Kinyarwanda to English | |
| def translate(text): | |
| # Tokenize the text using the __call__ method | |
| model_inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True) | |
| # Perform the translation | |
| gen = model.generate(**model_inputs) | |
| # Decode the generated tokens to string | |
| translation = tokenizer.batch_decode(gen, skip_special_tokens=True) | |
| return translation[0] | |
| # Create a Gradio interface | |
| iface = gr.Interface( | |
| fn=translate, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter Text in Kinyarwanda..."), | |
| outputs=gr.Textbox() | |
| ) | |
| # Launch the interface | |
| iface.launch(debug=True,inline=False) | |