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#python3
#pytorch
#build a text summarizer using hugging face and gradio
import gradio as gr
import transformers
from transformers import BartTokenizer, BartForConditionalGeneration
model = BartForConditionalGeneration.from_pretrained('facebook/bart-large-cnn')
tokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
def bart_summarizer(input_text):
input_text = tokenizer.batch_encode_plus([input_text], max_length=1024, return_tensors='pt')
summary_ids = model.generate(input_text['input_ids'], num_beams=4, max_length=100, early_stopping=True)
output = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]
return output[0]
gr.Interface(fn=bart_summarizer, inputs=gr.inputs.Textbox(lines=7, placeholder="Enter some long text here"), outputs="textbox", live=True).launch()
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