| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| tokenizer = AutoTokenizer.from_pretrained("ieuniversity/sciencebrief_translation") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("ieuniversity/sciencebrief_translation") | |
| def translate(text): | |
| input_ids = tokenizer(text, return_tensors="pt", truncation=True)['input_ids'] | |
| output_ids = model.generate(input_ids) | |
| output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True) | |
| return output_text | |
| iface_translate = gr.Interface( | |
| fn=translate, | |
| inputs=gr.inputs.Textbox(lines=10, label="Input Text"), | |
| outputs=gr.outputs.Textbox(label="Translation"), | |
| title="ScienceBrief Translation", | |
| description="Translate any Spanish text to English using our ScienceBrief model", | |
| theme="compact" | |
| ) | |
| iface_translate.launch() | |