Using Hugging Face Transformers, GPT Neo Writing

The recent pace of artificial intelligence development is nothing short of revolutionary.
Especially in the field of Natural Language Processing (NLP), various models have emerged,
altering the communication methods between humans and machines. Today, we will practice
text generation using the ‘GPT-Neo’ model with the ‘Transformers’ library from Hugging Face.

Table of Contents

1. Introduction to GPT-Neo

GPT-Neo is a large-scale language model developed by a research group called EleutherAI.
This model is based on OpenAI’s GPT (GPT-2, GPT-3) and is used for natural language generation
and various language understanding tasks. GPT-Neo boasts over 2.7 billion parameters and
demonstrates advanced language comprehension capabilities. This model can generate text on
various topics, making it a practical tool for many people.

2. Hugging Face Library

Hugging Face is known for providing a variety of models and toolkits related to natural language
processing. The ‘Transformers’ library is compatible with PyTorch and TensorFlow, making it
easy to use several powerful language models. This library offers the following features:

  • Access to pre-trained models
  • Model training and evaluation
  • Text preprocessing and dataset management
  • Easy API usage

3. Environment Setup

First, to use the GPT-Neo model, you need to install Python and the Hugging Face Transformers
library. Follow these steps:

3.1. Installing Python

If Python is not installed, download and install the latest version from the
official Python website. After installation,
you can check if Python is installed correctly in the terminal (cmd) or console with the
following command:

python --version

3.2. Installing the Hugging Face Transformers Library

Next, install the Transformers library. You can do this using pip with the following command:

pip install transformers torch

This command installs the ‘transformers’ library and PyTorch. PyTorch is a framework for deep
learning, used for model training and inference.

4. Using the GPT-Neo Model

The environment setup is now complete. Let’s learn how to use the GPT-Neo model.

4.1 Comic Writing Example

The code below is an example of generating a short story about a comic using the GPT-Neo model:


from transformers import GPTNeoForCausalLM, GPT2Tokenizer

# Load model and tokenizer
model_name = "EleutherAI/gpt-neo-2.7B"
tokenizer = GPT2Tokenizer.from_pretrained(model_name)
model = GPTNeoForCausalLM.from_pretrained(model_name)

# Input text
input_text = "On a summer day, three friends went on a trip to the seaside."

# Tokenize the text and input it to the model
input_ids = tokenizer.encode(input_text, return_tensors="pt")
output = model.generate(input_ids, max_length=100, num_return_sequences=1)

# Decode the generated text
generated_text = tokenizer.decode(output[0], skip_special_tokens=True)

print("Generated Text:")
print(generated_text)

4.2 Code Analysis

Now let’s look at each part of the code. First, we import the necessary libraries and load
the pre-trained GPT-Neo model and tokenizer called ‘EleutherAI/gpt-neo-2.7B’.
Next, we define input_text, which is the starting point for text generation.
This text serves as the initial input for generation.

Then, we use the tokenizer.encode method to tokenize the input text, followed
by calling the model.generate method to obtain the generated text. The
max_length parameter defines the maximum number of tokens to generate.
Finally, the generated text is converted to a human-readable format using the
tokenizer.decode method.

4.3 Results and Applications

When you run the above code, a story about the adventures the friends might have on a summer
day at the beach will be generated. In this way, the GPT-Neo model can create creative stories
based on the initial text provided. The generated stories can be used for various content
creation purposes, such as blog posts, novels, and scripts.

5. Conclusion

Today, we explored the process of generating text using the GPT-Neo model with the Hugging Face
Transformers library. GPT-Neo is a powerful tool that can be easily used with a simple script,
and it can be applied in various fields. We encourage you to utilize this library to create
creative content. If you have any questions or need help, feel free to leave a comment!