⚡ Live Sandbox: AI Dev Tool: Nicholas Polson has authored

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```python
# AI Dev Tool: TurboGPT CLI Automation Tool
# Description: A command-line interface for training and deploying TurboGPT models
# Author: [Your Name]

import argparse
import os
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

def train_turbo_gpt(model_name: str, train_data: str, output_dir: str, num_train_steps: int = 1000):
    """
    Train a TurboGPT model on the given training data.

Args:
    - model_name (str): The name of the TurboGPT model to train.
    - train_data (str): The path to the training data file.
    - output_dir (str): The directory to save the trained model.
    - num_train_steps (int): The number of training steps. Defaults to 1000.
    """
    # Load the model and tokenizer
    model = AutoModelForCausalLM.from_pretrained(model_name)
    tokenizer = AutoTokenizer.from_pretrained(model_name)

# Load the training data
    with open(train_data, 'r') as f:
        train_data = [line.strip() for line in f.readlines()]

# Preprocess the training data

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