| 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) |