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It is frustrating when you have worked on a lengthy message to chat gpt to then read: “The message you submitted was too long, please reload the conversation and submit something shorter.” This means you’ve exceeded the token limit, and the message can't be processed until it's within the acceptable range. But even if the message was not too long, are you aware of that if your message was quite long, it limits the answering result? For that reason, Understanding the token system used by GPT models can help avoid this inconvenience, ensuring a smoother and more efficient interaction with the AI.
Tokens are the basic units that GPT (Generative Pre-trained Transformer) models use to understand and process text. They are groups of characters, which sometimes align with words, but not always. For example, "a" is considered one token, and "apple" is also considered one token.Their count is not always equal to the word count because they can include punctuation signs, special characters, or emojis.
To count tokens, you can use a tokenizer tool. The algorithm will divide the text into tokens and count them, providing an accurate token count for any given text. OpenAI provides an official tokenizer that can be used for this purpose.
The ratio of words to tokens is language-dependent. For instance:
| Language | Sentence | Words | Tokens | Characters |
|---|---|---|---|---|
| English | I'm learning a new language and it is fun | 9 | 10 | 41 |
| German | Ich lerne eine neue Sprache und es macht Spaß | 9 | 16 | 44 |
| French | J’apprends une nouvelle langue et c’est amusant | 9 | 21 | 47 |
| Spanish | Estoy aprendiendo un nuevo idioma y es muy divertido | 9 | 18 | 52 |
The GPT model processes text in terms of tokens. A token can range from a single character to a whole word. This model can handle up to 4096 tokens in a single request, which encompasses both the input and output. If the input tokens exceed the model's limit, you will receive an error message, and the model will not process the request until the input is within the acceptable token range. If your input is within the limit but leaves very little room for the output, the response from the model may be cut short, possibly leading to the loss of valuable information. The actual character count could be less than or more than 4096, depending on the text.