How to Use GPT to Generate AI-Based Blog Content – Python Implementation

Blogging is a method in which individual content creator and business share their knowledge on a variety of topics in textual form. It is a valuable tool to share your views and connect with a larger audience.

Business uses blog post to generate leads, sell their products or courses and reach their business goals. It is also a good source of income for individual bloggers.

As we know the application of artificial intelligence is increasing in various domains, it is solving various business problems. So can we use artificial intelligence in writing blogs?

Can AI Write Blogs?

The answer is yes but how? Have you heard of Natural Language Processing?

Natural Language Processing is a subdomain of AI that provides computers with the ability to understand human language and generate meaningful text as a response. It majorly works with textual data and can understand different languages like English, French etc.

In the last few years, a lot of work has been done on deep-learning models that work with text. The models like Bert and Transformer have been major breakthroughs in the NLP domain.

GPT-2 and GPT-3 which stand for Generative Pre-trained Transformer generation 2 and 3 respectively have the capability to generate rich content which can be posted online.

What Can AI Do For You as a Writer?

If you are regularly writing content on blogs or any other social media platform, AI can be very helpful for you. Below are a few tasks AI can do for you as a writer.

  • Generate a heading for your post.
  • Generate catchy taglines.
  • Generate important keywords for the selected topic.
  • Optimize content for search engines.
  • Generate a complete blog post with a few starting sentences.

All the applications mentioned above are crucial tasks for you as a content writer. Think of how much time and effort can be saved if you are assisted by AI.

Later in this article, we will also learn how to use GPT to create content for your next blog post. If this sounds interesting to you, keep reading this article till the end.

Best AI Writing Software

There are many AI tools already available in the market which can assist you in writing. Below is a list of some of the best AI writing software.

A Step-Wise Guide for Creating a Blog Post Using Python

Let us understand how to generate content for your next blog post using GPT in Python. If you want to create a project in python which includes AI, this can be a great idea. Just follow the below steps.

Before starting with the code part, let us understand GPT first.


Generative Pre-trained Transformer is a built-in neural network model developed using a large amount of data from the internet. It is capable of generating the content of the required length by taking a small amount of text as input.

Text Generation Using GPT

Finally, we are here to use some code in python to generate content. We will see a 6-step process to generate text using GPT.

Step 1: Install the Package

Install the transformers package developed by Huggingface using the below command.

pip install transformers

Step 2: Import Libraries

Import GPT2Tokenizer and GPT2LMHeadModel libraries.

from transformers import GPT2Tokenizer, GPT2LMHeadModel

Step 3: Get Tokenizer Object

Machine learning models cannot understand textual data. Therefore, we need to convert it into numerical values. A built-in tokenizer GPT2Tokenizer can be used to download the tokenizer associated with the model we picked gpt2-large and instantiate it.

GPT2Tokenizer has been trained to treat spaces as part of the tokens such that the same word will be treated differently depending on its location if it is at the start of a sentence (without space) or in between the sentence (with space).

tokenizer = GPT2Tokenizer.from_pretrained('gpt2-large')

Step 4: Get Model Object

The model object can be created using gpt2-large and the tokenizer object created in the previous step with the from_pretrained function.

model = GPT2LMHeadModel.from_pretrained('gpt2-large', pad_token_id=tokenizer.eos_token_id)

Step 5: Prepare the Prefix Text and Create Tokens

The input text is tokenized using the tokenizer created in step 3.

initial_text = r 'Data Science and Machine Learning'
input_tokens= tokenizer(initial_text, return_tensors='pt').input_ids

Step 6: Generate the Content with a Contrastive Search

Let’s generate the content using the generate function. It takes a few parameters:

  • input_tokens= tokens generated for input text
  • penalty_alpha= hyperparameter alpha
  • top_k= top k content
  • max_length= maximum length of the content
print("Output:\n" + 100 * '-')
content = model.generate(input_tokens, penalty_alpha=0.6, top_k=4, max_length=512)
print("" + 100 * '-')


Data Science and Machine Learning The course is divided into three parts: Data Science, Machine Learning and Big Data. In each of these sections you will learn how to build a model that predicts the data, analyze the data and make predictions based on the model. The goal is to be able to use this model to solve real-world problems that are related to data science and machine learning. Data Science This section introduces you to the basics of data science and how it can be applied to your day to day work. You will learn how to use Python, R, Matlab and Pandas to analyze data and perform statistical analyses. You will also learn how to create data visualizations and explore the data in a variety of ways. Machine Learning This section introduces you to the basics of machine learning and how it can be applied to your day to day work. You will learn how to use Python, R, Matlab and Pandas to analyze data and perform statistical analyses. You will also learn how to create data visualizations and explore the data in a variety of ways. Brief overview of the course content The following is a brief overview of the content of the course. For more information about the course, please visit Introduction to Python Python is a high-level programming language that provides a simple and easy-to-use interface to the computer. Python is an object-oriented language, meaning that objects are represented as data structures and functions that manipulate data. The Python standard library contains over 1,000 modules, which are designed to make it easy to work with data and data structures. Python has a large and growing community of users, and there are many resources for learning Python. The University of Massachusetts Amherst has a Python User Group (PUG), which meets every Wednesday at 7:30 PM in Room 6A of the Student Union (SUNY Amherst). The PUG is a great place to meet other Python users and get help with Python problems. You can sign up for the mailing list by sending an email to R R is a statistical computing language and graphical user interface (GUI) for scientific computing. R is widely used in research and academia, and it is the language of choice for many of the world’s most prominent scientific and engineering organizations such as NASA, the National Institutes of Health

How Will Writers Get Affected by AI?

Artificial Intelligence writers are not here to completely swap human content writers, they will rather act as their assistants and will ease their work. Hence writers can leverage the benefits of AI assistants.

What is the Future of Writing AI?

AI has not come into existence to escape, it is here to stay. The current capabilities of AI tools will surely be enhanced. Therefore, AI has a good scope in content generation in the future. It will be capable of generating content which is rich in quality, informative, more search engine optimized and targeting a larger audience.

Pros of AI For Blog Writing

AI writing can be a very useful tool for you as a writer. Below are a few areas where it can help you:

  • It checks plagiarism which is a major concern for writing blogs.
  • AI can evaluate the readability of your content and quickly scan for grammar.
  • AI can provide the right keywords for the selected topic.
  • AI language translation feature can convert a blog post into different languages.
  • It saves time and effort.

Cons of AI For Blog Writing

Completely depending on the AI writer for creating a blog is still not possible. Below are some reasons:

  • It requires human involvement.
  • It can include bias.
  • It lacks human personality touch.

End Notes

In this article, we have seen how AI can be useful to bloggers but one thing is for sure, AI cannot replace human writers entirely. Blog articles require explaining a concept to humans which can be done only by another human. AI tools can simplify your work by being your assistant.

We have also learnt python code which can generate content. Now you are ready to build your own blog writing tool. This tool can be integrated with a mobile app or a website.

I hope you found this article informative and interesting at the same time. I regularly write articles on topics related to artificial intelligence and data science. To stay updated, follow me on Linkedin.

Thank You and Happy Learning!