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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn")
def text_summarize(article):
inputs = tokenizer(article, return_tensors = 'pt')
output = model.generate(inputs.input_ids,
max_new_tokens = 200,
do_sample = True,
top_p = 0.9,
top_k = 50)
output_text = tokenizer.decode(output[0], skip_special_tokens=True)
return output_text
iface = gr.Interface(
fn = text_summarize,
inputs = gr.Textbox(label = "Article", lines = 8, placeholder = "Paste your text here.."),
outputs = gr.Textbox(label = "Summarized Text", lines = 5)
)
iface.launch()
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