File size: 2,283 Bytes
4188a3b 3b25080 4188a3b 34cfb12 3b25080 4188a3b 875c380 f48907d 875c380 2403a13 875c380 8d74675 67c15e0 fd7b525 67c15e0 96e1d4f 70933ec 96e1d4f 4188a3b 9133fa2 871bae2 9133fa2 67c15e0 926e92f fd7b525 926e92f 8d74675 3ed518c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
from transformers import pipeline, set_seed
import gradio as grad
import random
import re
gpt2_pipe = pipeline('text-generation', model='succinctly/text2image-prompt-generator')
with open("name.txt", "r") as f:
line = f.readlines()
def generate(starting_text):
for count in range(6):
seed = random.randint(100, 1000000)
set_seed(seed)
# If the text field is empty
if starting_text == "":
starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()
starting_text: str = re.sub(r"[,:\-–.!;?_]", '', starting_text)
print(starting_text)
response = gpt2_pipe(starting_text, max_length=random.randint(60, 90), num_return_sequences=8)
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((":", "-", "—")) is False:
response_list.append(resp)
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 == 5:
return response_end
txt = grad.Textbox(lines=1, label="English", placeholder="English Text here")
out = grad.Textbox(lines=6, label="Generated Text")
examples = [["mythology of the Slavs"], ["All-seeing eye monitors these world"], ["astronaut dog"],
["A monochrome forest of ebony trees"], ["sad view of worker in office,"],
["Headshot photo portrait of John Lennon"], ["wide field with thousands of blue nemophila,"]]
title = "Aiconvert.online"
description = "Ai Image Prompt Generator."
article = "<div><center><img src='' 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).queue(concurrency_count=1, api_open=False).launch(show_api=False, show_error=True)
|