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from transformers import pipeline, set_seed
import gradio as grad
import random
gpt2_pipe = pipeline('text-generation', model='succinctly/text2image-prompt-generator')
def generate(starting_text):
seed = random.randint(1, 100000)
set_seed(seed)
while True:
response = gpt2_pipe(starting_text, max_length=30, num_return_sequences=random.randint(5, 15))
if starting_text != response[1]['generated_text'].strip():
print(f"Repeat: {response}")
else:
return response[1]['generated_text']
txt = grad.Textbox(lines=1, label="English", placeholder="English Text here")
out = grad.Textbox(lines=1, label="Generated Text")
grad.Interface(fn=generate, inputs=txt, outputs=out,
allow_flagging='never',
cache_examples=False,
theme="default").launch(enable_queue=True, debug=True) |