import gradio as gr import re from gradio.mix import Parallel from transformers import ( AutoTokenizer, AutoModelForSeq2SeqLM, ) def clean_text(text): text = text.encode("ascii", errors="ignore").decode( "ascii" ) # remove non-ascii, Chinese characters text = re.sub(r"\n", " ", text) text = re.sub(r"\n\n", " ", text) text = re.sub(r"\t", " ", text) text = text.strip(" ") text = re.sub( " +", " ", text ).strip() # get rid of multiple spaces and replace with a single return text modchoice_1 = "chinhon/pegasus-newsroom-malay_headlines" def headline_writer1(text): input_text = clean_text(text) tokenizer_1 = AutoTokenizer.from_pretrained(modchoice_1) model_1 = AutoModelForSeq2SeqLM.from_pretrained(modchoice_1) with tokenizer_1.as_target_tokenizer(): batch = tokenizer_1( input_text, truncation=True, padding="longest", return_tensors="pt" ) translated = model_1.generate(**batch) summary_1 = tokenizer_1.batch_decode(translated, skip_special_tokens=True) return summary_1[0] headline1 = gr.Interface( fn=headline_writer1, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Textbox(label=""), ) modchoice_2 = "chinhon/pegasus-multi_news-malay_headlines_02" def headline_writer2(text): input_text = clean_text(text) tokenizer_2 = AutoTokenizer.from_pretrained(modchoice_2) model_2 = AutoModelForSeq2SeqLM.from_pretrained(modchoice_2) with tokenizer_2.as_target_tokenizer(): batch = tokenizer_2( input_text, truncation=True, padding="longest", return_tensors="pt" ) translated = model_2.generate(**batch) summary_2 = tokenizer_2.batch_decode(translated, skip_special_tokens=True) return summary_2[0] headline2 = gr.Interface( fn=headline_writer2, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Textbox(label=""), ) Parallel( headline1, headline2, title="Malay News Headlines Generator", inputs=gr.inputs.Textbox( lines=20, label="Paste the first few paragraphs of a Malay language news story here, and choose from 2 suggested headlines", ), theme="darkdefault", ).launch(enable_queue=True)