app.py

import tensorflow as tf
import transformers

# Load the model
model = transformers.TFGPT2LMHeadModel.from_pretrained("souleater-diffusion.ckpt")

# Generate pictures using the model
def generate_picture(prompt):
    input_ids = transformers.preprocessing.text.text_to_sequence(prompt, model.tokenizer.tokenize)
    input_ids = tf.expand_dims(input_ids, 0)
    output = model.generate(input_ids)
    generated_text = model.tokenizer.decode(output[0], skip_special_tokens=True)
    return generated_text

# GUI to enter the prompts
from tkinter import *

root = Tk()
root.title("souleater-diffusion.ckpt Model")

prompt_entry = Entry(root)
prompt_entry.pack()

def generate_callback():
    prompt = prompt_entry.get()
    result = generate_picture(prompt)
    result_label.config(text=result)

generate_button = Button(root, text="Generate", command=generate_callback)
generate_button.pack()

result_label = Label(root, text="")
result_label.pack()

root.mainloop()