What are Tokens in the context of AI?
In the context of AI, tokens are the basic units of text or code that AI models use to process and generate language. These tokens can be characters, words, subwords, or other segments of text or code, depending on the chosen tokenization method or scheme
. Here are some key points about tokens in AI:
Tokenization: Tokenization is the process of splitting input and output texts into smaller units that can be processed by AI models. Tokens can be words, characters, subwords, or symbols, depending on the type and size of the model. Tokenization helps the model handle different languages, vocabularies, and formats, and reduces computational and memory costs.1
Types of tokens: Different models may use slightly different tokens, but here are some common token types:
- Word tokens: Individual words or phrases in the text.
- Sub-word tokens: Words broken down into smaller sub-word units.
- Punctuation tokens: Tokens representing various punctuation marks.
- Special tokens: Symbols serving specific roles within the model, such as classification or separation.
- Number tokens: Textual numbers converted into numerical tokens.
- Out-of-Vocabulary (OOV) tokens: Represent words not in the model's vocabulary.4
Token counting: Tokens are not necessarily equal to words or characters in terms of length. For example, in English, 1 token is approximately 4 characters or ¾ of a word. To count tokens in a text, you can use interactive tools like OpenAI's Tokenizer or libraries like Tiktoken, transformers, or gpt-3-encoder2.2
Token size and efficiency: Token size determines how much information an AI can process at once and influences its understanding of context. AI researchers are always working to optimize token size and efficiency, allowing models to tackle more extensive puzzles faster and more accurately.6
What is the difference between a token and a word in AI?
In the context of AI, there are some differences between tokens and words:
Tokens: Tokens are the basic units of text or code that AI models use to process and generate language. They can be characters, words, subwords, or other segments of text or code, depending on the chosen tokenization method or scheme. For example, in the sentence "I'd like," there are three tokens: "I," "'d," and "like," where the second token represents the contraction "would"2. Tokens are assigned numerical values or identifiers and are arranged in sequences or vectors, which are fed into or outputted from the model1.2
Words: Words, on the other hand, are the traditional units of language that we are familiar with. They are made up of one or more tokens and are the building blocks of sentences and phrases. Some words can be represented by a single token, while others may require multiple tokens. For instance, the word "everyday" can be broken down into two tokens: "every" and "day," while the word "joyful" consists of the tokens "joy" and "ful".1
If I prompt AI to meet a certain number of tokens or characters, will it be able to reach them?
When using AI to generate text, there are token and character limits that can affect the length of the output. Here's what you need to know about these limits:
Token limits: Tokens are the individual units of text that the AI model processes. The number of tokens in a prompt and its completion affects the total token count. Different AI models have different token limits, which can range from a few hundred to a few thousand tokens. For example, the GPT-3 model has a maximum token limit of 40961. If your prompt is close to the token limit, the generated output may be cut off or truncated.6
Character limits: Characters are the actual letters, numbers, and symbols in the text. The character limit can vary depending on the AI tool or platform you're using. For example, ChatGPT has a character limit of 4096 for text prompts. If your text exceeds the character limit, you may need to shorten it or split it into multiple parts.6
Check the token count: Use OpenAI's Tokenizer tool or other libraries like Tiktoken, transformers, or gpt-3-encoder to calculate the number of tokens in your text. This will help you stay within the token limit and adjust your input accordingly.1
Be frugal with your text: If you're approaching the token or character limit, try to remove unnecessary words, spaces, or punctuation to make your text more concise.2
Consider the AI model's limitations: Some AI models may have lower token or character limits than others. If you need to generate a longer text, you may need to use a different model or break down your input into smaller chunks.4
What is the maximum number of tokens that can be used in an AI prompt?
How does the token limit affect the length of an AI response?
Are there any AI models that do not have a token limit?