What is OpenAI Tokenizer and How to Use It?

It’s essential to understand what tokens mean if you want to use OpenAI’s models or APIs. Tokens are essentially pieces of words. Before the OpenAI’s APIs process the prompts, the input is broken down into tokens. These tokens aren’t necessarily split exactly where words start or end – they can include trailing spaces and even sub-words.

Understanding tokens, their value, and how to count them is critical, particularly when using OpenAI’s language models like GPT-3, Codex, and GPT-4.

What are Tokens?

Think of tokens as the building blocks of language. They are pieces of text that language models read and write. In English, a token can be as short as one character or as long as one word (e.g., “b” or “banana”). In some languages, tokens can be even shorter or longer.

The total number of tokens in an API call affects the cost, duration, and whether the call works at all. This is because you pay per token, and there’s a maximum limit to the number of tokens a model can process.

Why is Counting Tokens Important?

Understanding and managing your token count is crucial because OpenAI charges per token. Knowing your token usage can help you estimate the cost of using OpenAI’s models. Additionally, it helps ensure that your API calls do not exceed the model’s maximum token limit.

What is OpenAI Tokenizer?

OpenAI tokenizer is a tool that breaks down your input into tokens. This tokenization process is essential for language models as it allows them to understand and generate responses based on statistical relationships between tokens.

How to Use OpenAI Tokenizer?

Here is a step-by-step guide on how to use the OpenAI tokenizer:

1. Visit https://platform.openai.com/tokenizer.
2. Choose from GPT-3 or Codex models. Codex uses a different encoding that more effectively counts spaces.
3. Enter the text you want to calculate tokens for.
4. After entering the text, the total character count and token count will be automatically calculated.
5. You can also view how the tokens are grouped in your text with the help of colored elements.

How to Count Tokens in Python?

For a programmatic interface for tokenizing text in Python, there is a Python package called Tiktoken. It is a fast BPE tokenizer package specifically designed for OpenAI models. It is between 3-6x faster than comparable open-source tokenizers.

How to use Tiktoken package?

In order to use Tiktoken package in Python, follow the steps provided below:

1. Install tiktoken: use “%pip install –upgrade tiktoken” command
2. Import tiktoken in your Python file
3. Load an encoding: Use tiktoken.encoding_for_model() method to load GPT-3 or GPT-4 models.
4. Turn text into tokens with encoding.encode() method. For example use encoding.encode("How many tokens are there in this text") to calculate.

How to Count Tokens in other languages?

You can also use other libraries to calculate tokens in the programming languages.

• For javascript: Use OpenAI’s GPT-3-Encoder. It is a node package manager that can be used to count tokens in JavaScript using Node.js.
• For Java: Use jtokkit library
• For .Net: Use SharpToken library
• For PHP: Use GPT-3 Encoder

How Much Does OpenAI API Cost?

OpenAI offers different models at varying price points. Each model has a range of capabilities, with GPT-4 being the most expensive. The cost also depends on the tokens used in your API calls. You can find details about the pricing of using the GPT-4 model’s API.