| import gradio as gr |
| from transformers import EncoderDecoderModel, BertTokenizer |
|
|
| model = EncoderDecoderModel.from_pretrained("abdulhamed/AraBert-summarize") |
| tokenizer = BertTokenizer.from_pretrained("abdulhamed/AraBert-summarize") |
|
|
| def summarize_article(article): |
| input_ids = tokenizer(article, return_tensors="pt", truncation=True, padding=True).input_ids |
| generated = model.generate(input_ids)[0] |
| summary = tokenizer.decode(generated, skip_special_tokens=True) |
| return summary |
|
|
| iface = gr.Interface( |
| fn=summarize_article, |
| inputs=gr.Textbox(lines=10, label="Article"), |
| outputs=gr.Textbox(label="Summary"), |
| title="AraBERT Summarization" |
| ) |
|
|
| iface.launch() |
|
|
