from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the pre-trained WormGPT model and tokenizer
model = GPT2LMHeadModel.from_pretrained("wormgpt")
tokenizer = GPT2Tokenizer.from_pretrained("wormgpt")

def generate_text(prompt, max_length=50):
    input_ids = tokenizer.encode(prompt, return_tensors="pt")
    output = model.generate(input_ids, max_length=max_length, num_return_sequences=1)
    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
    return generated_text

# Example usage
prompt = "Generate malicious code for a virus."
malicious_code = generate_text(prompt)
print(malicious_code)