2.3: Seeing In Action

Simple Hands On: Text Generation with GPT

Let’s write some code to generate text using a pre-trained GPT model. We’ll use the transformers library by Hugging Face, which provides easy access to many pre-trained models.

Step 1: Install the Required Libraries

You’ll need Python installed on your machine along with the following packages:

  • transformers (from Hugging Face)
  • torch (PyTorch backend)
pip install transformers torch

Step 2: Write the Code

from transformers import pipeline

# Load a pre-trained GPT-2 model for text generation
generator = pipeline('text-generation', model='gpt2')

# Generate text
prompt = "The future of AI is"
output = generator(prompt, max_length=50, num_return_sequences=1)

# Print the generated text
print(output[0]['generated_text'])

Explanation:

  • pipeline('text-generation', model='gpt2'): Loads the GPT-2 model for text generation.
  • prompt: The starting text for generation.
  • max_length: The maximum length of the generated text.
  • num_return_sequences: The number of sequences to generate.

Output Example:

The future of AI is bright, with advancements in natural language processing, computer vision, and robotics. As AI continues to evolve, it will transform industries, improve healthcare, and enhance our daily lives.

Experiment with Different Prompts

Try changing the prompt variable to see how the model responds. For example:

  • “In a world where robots rule,”
  • “Once upon a time, there was a”
  • “The secret to happiness is”

Practice Yourself

  1. Run the Code: Execute the text generation code and experiment with different prompts.
  2. Explore Other Models: Replace gpt2 with other models like EleutherAI/gpt-neo-1.3B or gpt-j (if available).

For list of available models, check Hugging Face Model Hub.

generator = pipeline('text-generation', model='EleutherAI/gpt-neo-1.3B')
  1. Read More: Familiarize yourself with the Hugging Face documentation and explore other tasks like translation, summarization, and question answering.

Additional Resources