initial commit

app.py

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+import gradio as gr
+import transformers
+from transformers import BartTokenizer, BartForConditionalGeneration
+model_name = 'facebook/bart-large-cnn'
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+def summarize(inp):
+    inp = inp.replace('\n','')
+    inp = tokenizer.encode(inp, return_tensors='pt', max_length=1024)
+    summary_ids = model.generate(inp, num_beams=4, max_length=150, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+gr.Interface(fn=summarize, inputs=gr.inputs.Textbox(lines=7, label="Input Text"), outputs="text").launch(inline=False)

requirements.txt

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+transformers
+torch