| 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, 10000000) | |
| set_seed(seed) | |
| response= gpt2_pipe(starting_text, max_length=20, num_return_sequences=5) | |
| return response[1] | |
| 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) |