# Import necessary libraries
import torch
from transformers import GPT2Tokenizer, GPT2Model
import numpy as np

# Load pre-trained model and tokenizer
model_name = "gpt2"  # You can use other NSFW models if available
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPT2Model.from_pretrained(model_name)

# Define function to generate NSFW images
def generate_nsfw_image(prompt, max_length=50, num_return_sequences=1):
    input_ids = tokenizer.encode(prompt, return_tensors="pt")
    with torch.no_grad():
        output = model.generate(
            input_ids=input_ids,
            max_length=max_length,
            num_return_sequences=num_return_sequences,
            do_sample=True,
            temperature=0.7,
        )
    nsfw_images = [tokenizer.decode(seq, skip_special_tokens=True) for seq in output]
    return nsfw_images

# Example usage:
prompt = "Two people engaging in explicit activity"
nsfw_images = generate_nsfw_image(prompt)
print("Generated NSFW Images:")
print(nsfw_images)