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| from newspaper import Article | |
| from newspaper import Config | |
| import gradio as gr | |
| from transformers import MBartForConditionalGeneration | |
| from transformers import AutoTokenizer | |
| model_name = "haotieu/vietnamese-summarization" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = MBartForConditionalGeneration.from_pretrained(model_name) | |
| def extract_article_text(url): | |
| USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:78.0) Gecko/20100101 Firefox/78.0' | |
| config = Config() | |
| config.browser_user_agent = USER_AGENT | |
| config.request_timeout = 20 | |
| article = Article(url, config=config) | |
| article.download() | |
| article.parse() | |
| text = article.text | |
| return text | |
| def news_summarizer(url): | |
| text = extract_article_text(url) | |
| input_ids = tokenizer.encode_plus(text, return_tensors='pt', max_length=512, truncation=True, padding=True)['input_ids'] | |
| summary_ids = model.generate(input_ids,max_length=128,min_length= 64) | |
| summaries = [tokenizer.decode(s, skip_special_tokens=True) for s in summary_ids] | |
| return summaries[0] | |
| sample_url = 'https://vnexpress.net/them-hai-nuoc-rut-nhan-vien-su-quan-tai-ukraine-4420581.html' | |
| desc = 'This app uses BARTpho model by VinAI to summarize the text of a news article.' | |
| summarizer_interface = gr.Interface(fn = news_summarizer, inputs="text", outputs = "text",title="vietnamese news summarizer", | |
| theme = 'huggingface',examples=[sample_url],description=desc | |
| ) | |
| summarizer_interface.launch(inline=False) |