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''' | |
A script that uses gradio to make a web app that takes in a dialog and outputs a summary. | |
Import a huggingface model. | |
''' | |
import gradio as gr | |
from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM | |
MODEL_NAME = "Firefly777a/bart-large-samsum-candice-set-summary-3ep-3" | |
# Import the model | |
summarizer = pipeline("summarization", model=MODEL_NAME, tokenizer=MODEL_NAME) | |
# tokenizer = AutoTokenizer.from_pretrained(PRETRAIN_MODEL_NAME) | |
# Define the function that will be used by the web app | |
def summarize_dialog(dialog, max_length): | |
# Summarize the dialog | |
summary = summarizer(dialog, max_length=max_length, min_length=10, do_sample=False) | |
# Return the summary | |
return summary[0]['summary_text'] | |
# Define the web app & launch | |
gr.Interface(fn=summarize_dialog, | |
inputs=["text", | |
gr.Slider(32, 256, value=128) | |
], | |
outputs="text").launch() |