app.py

import gradio as gr
from transformers import pipeline
from transformers import pipeline
import re
from utils import grammatical_cleaning

dante = pipeline('text-generation',model='.', tokenizer='GroNLP/gpt2-small-italian-embeddings')

title = "Dante's style text generation"
description = """

Play with Dante's style text generation. Base model is gpt-2-small-italian, fine-tuned on Dante Alighieri's corpus. 



def get_text(input):

	generated = dante(input, max_length=128)[0]['generated_text']

	generated = grammatical_cleaning(generated)

	return generated



iface = gr.Interface(fn=get_text, inputs="text", outputs="text",examples=sample_text, description=description)

iface.launch()