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from transformers import pipeline, set_seed | |
import gradio as grad, random, re | |
gpt2_pipe = pipeline('text-generation', model='Gustavosta/MagicPrompt-Stable-Diffusion', tokenizer='gpt2') | |
with open("ideas.txt", "r") as f: | |
line = f.readlines() | |
def generate(starting_text): | |
for count in range(4): | |
seed = random.randint(100, 1000000) | |
set_seed(seed) | |
if starting_text == "": | |
starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize() | |
starting_text: str = re.sub(r"[,:\-β.!;?_]", '', starting_text) | |
print(starting_text) | |
response = gpt2_pipe(starting_text, max_length=(len(starting_text) + random.randint(60, 90)), num_return_sequences=4) | |
response_list = [] | |
for x in response: | |
resp = x['generated_text'].strip() | |
if resp != starting_text and len(resp) > (len(starting_text) + 4) and resp.endswith((":", "-", "β")) is False: | |
response_list.append(resp+'\n') | |
response_end = "\n".join(response_list) | |
response_end = re.sub('[^ ]+\.[^ ]+','', response_end) | |
response_end = response_end.replace("<", "").replace(">", "") | |
if response_end != "": | |
return response_end | |
if count == 4: | |
return response_end | |
txt = grad.Textbox(lines=1, label="Initial Text", placeholder="English Text here") | |
out = grad.Textbox(lines=4, label="Generated Prompts") | |
examples = [] | |
for x in range(8): | |
examples.append(line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()) | |
title = "Stable Diffusion Prompt Generator" | |
description = 'This is a demo of the model series: "MagicPrompt", in this case, aimed at: Stable Diffusion. To use it, simply submit your text or click on one of the examples.<b><br><br>To learn more about the model, go to the link: https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion<br>' | |
article = "<div><center><img src='https://visitor-badge.glitch.me/badge?page_id=magicprompt_Stable Diffusion' alt='visitor badge'></center></div>" | |
grad.Interface(fn=generate, | |
inputs=txt, | |
outputs=out, | |
examples=examples, | |
title=title, | |
description=description, | |
article=article, | |
allow_flagging='never', | |
cache_examples=False, | |
theme="default").launch(enable_queue=True, debug=True) | |