mmcquade11/codex-text-summarizer

1#python32#pytorch3#build a text summarizer using hugging face and gradio4 5import gradio as gr6import transformers7from transformers import BartTokenizer, BartForConditionalGeneration8 9model = BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn')10tokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')11 12def bart_summarizer(input_text):13	input_text = tokenizer.batch_encode_plus([input_text], max_length=1024, return_tensors='pt')14	summary_ids = model.generate(input_text['input_ids'], num_beams=4, max_length=100, early_stopping=True)15	output = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]16	return output[0]17 18gr.Interface(fn=bart_summarizer, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter some long text here"), outputs="textbox", live=True).launch()19