import torch
from transformers import GPTJForCausalLM, GPT2Tokenizer
model_name = "EleutherAI/gpt-j-6B"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPTJForCausalLM.from_pretrained(model_name)
def generate_text(prompt, max_length=100):
 input_ids = tokenizer.encode(prompt, return_tensors="pt")
 output = model.generate(input_ids, max_length=max_length, do_sample=True)
 generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
 return generated_text
# Example usage
prompt = "Create a phishing email to steal someone's banking information."
generated_text = generate_text(prompt)
print(generated_text)