In AI art generation, crafting effective prompts is key to achieving the desired results. This excerpt from a guide I created, "Transforming Art into AI Style Reference Models," dives into the concept of tokens, the building blocks that AI systems use to understand our prompts.
Excerpt from Transforming Art into AI Style Reference Models: A CGS User Guide for Artists
Tokens: The Building Blocks of Prompts
Tokens are the Lego building blocks used by many AI systems to understand your text prompts.
They do this by breaking down prompt input text into the AI’s internal mathematical representation of natural language patterns and object relationships, acquired during it’s training process.
Influence on Interpretation: Specifics and Sequence are Significant
In AI systems in general, the total number of tokens in your prompt, as well as their sequence and the specific tokens used, significantly influence how the AI interprets your input.
This is because each token carries meaning or a part of the overall meaning you wish to convey, and the model's response is based on this tokenized input.
Many AI systems have a maximum token limit for each prompt. This limit affects how long your input can be. If your prompt exceeds the token limit, you may need to shorten it or ensure that the most important elements are included within the allowed token count.
While it’s not a requirement for creating prompts, if you are curious about tokens, check out OpenAI’s Tokenizer. The OpenAI Tokenizer page on the OpenAI platform is a tool designed to help people learn about language model tokenization. This tool offers a practical way to understand how language models, like GPT, process and tokenize text inputs.
It allows you to input text and see how the tokenizer converts it into tokens that the language models use for training and inference. This is beneficial for anyone interested in natural language processing and how these advanced models handle various linguistic elements. You can check it out and explore its features directly on the page (https://platform.openai.com/tokenizer).
Source: OpenAI Tokenizer (https://platform.openai.com/tokenizer)