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