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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() | |