|
|
|
import torch |
|
from transformers import GPT2Tokenizer, GPT2Model |
|
import numpy as np |
|
|
|
|
|
model_name = "gpt2" # You can use other NSFW models if available |
|
tokenizer = GPT2Tokenizer.from_pretrained(model_name) |
|
model = GPT2Model.from_pretrained(model_name) |
|
|
|
|
|
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 |
|
|
|
|
|
prompt = "Two people engaging in explicit activity" |
|
nsfw_images = generate_nsfw_image(prompt) |
|
print("Generated NSFW Images:") |
|
print(nsfw_images) |
