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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 = str(gpt2_pipe(starting_text, max_length=30, num_return_sequences=random.randint(5, 15))).strip() | |
if starting_text != response[1]['generated_text']: | |
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) |