| import gradio as gr | |
| from transformers import T5ForConditionalGeneration, T5Tokenizer | |
| model_name = 'jbochi/madlad400-3b-mt' | |
| model = T5ForConditionalGeneration.from_pretrained(model_name, device_map="auto") | |
| tokenizer = T5Tokenizer.from_pretrained(model_name) | |
| def translate_to_russian(input_text): | |
| full_input_text = "<2ru>" + input_text | |
| input_ids = tokenizer(full_input_text, return_tensors="pt").input_ids.to(model.device) | |
| outputs = model.generate( | |
| input_ids=input_ids, | |
| max_length=256, | |
| num_beams=4, | |
| no_repeat_ngram_size=2, | |
| length_penalty=1.2 | |
| ) | |
| translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return translated_text | |
| # Define Gradio interface | |
| iface = gr.Interface( | |
| fn=translate_to_russian, | |
| inputs=[gr.Textbox(lines=10, placeholder="Enter text to translate")], | |
| outputs="textbox", | |
| title="Translate to Russian", | |
| description="Enter text in English and get the Russian translation.", | |
| ) | |
| # Launch the interface | |
| iface.launch(debug=True) | |