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import gradio as gr | |
from transformers import pipeline | |
def generate_story(story): | |
story_gen = pipeline("ner", "dbmdz/bert-large-cased-finetuned-conll03-english", grouped_entities=True) | |
story_expanded = story_gen(story) | |
return str(story_expanded) | |
demo = gr.Interface ( | |
fn=generate_story, | |
description="Story generation with GPT-2", | |
examples=[ | |
["Adventurer is approached by a mysterious stranger in the tavern for a new quest."], | |
["He didn't remember the last time he had to run this fast as he jumped on to the bus."], | |
["Fate has it's own plans for the common man, which is why we philosophise on the observationg giving it our own interpretation."], | |
["The bear reached the river and spotted a school of fish. His hunger started taking its toll."] | |
], | |
inputs=[gr.Textbox(lines=7, label="Story URL")], | |
outputs=[gr.Textbox(lines=7, label="Story Summary")] | |
) | |
demo.launch(share=True) |