📌 Token Usage Summary
Token usage refers to the number of pieces of text, called tokens, that are processed by language models and other AI systems. Tokens can be as short as one character or as long as one word, depending on the language and context. Tracking token usage helps manage costs, performance, and ensures that the input or output does not exceed system limits.
🙋🏻♂️ Explain Token Usage Simply
Think of tokens like pieces of a puzzle, where each word or part of a word is one piece. The more pieces you use, the bigger the puzzle. In AI, each token counts towards how much information you can send or receive, just like a text message with a character limit.
📅 How Can it be used?
Token usage can be tracked to control costs and avoid exceeding limits when building chatbots or text analysis tools.
🗺️ Real World Examples
A company building a customer support chatbot monitors token usage to ensure they do not go over their monthly quota with the AI provider, helping to manage costs and maintain fast response times.
A developer creating a text summarisation tool checks token usage to ensure long documents are split properly, so the AI model can process the text without losing important information.
✅ FAQ
What is token usage and why does it matter?
Token usage refers to the number of text pieces, or tokens, that an AI system reads or generates. It is important because it helps keep track of how much information is being processed, which can affect how quickly and efficiently the system works, as well as the cost of using it.
How does token usage affect the cost of using AI tools?
Many AI services charge based on the number of tokens processed. If you use more tokens, it usually means higher costs. Keeping an eye on token usage can help you manage your expenses and avoid any surprises on your bill.
Is there a limit to how many tokens I can use with an AI model?
Yes, most AI systems have a maximum number of tokens they can handle at once. This limit ensures that the system runs smoothly and does not get overwhelmed. If your input or output goes over the limit, you might need to shorten your text or split it into smaller parts.
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