from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch

tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")

prompt = "Dale found the parking space he always used was taken, so he drove around the block again."
input_ids = tokenizer.encode(prompt, return_tensors="pt")

output = model.generate(
    input_ids,
    max_new_tokens=60,
    do_sample=True,
    temperature=0.9,
    top_k=40,
    top_p=0.95,
)

print(tokenizer.decode(output[0], skip_special_tokens=True))