Tokenlänge

Tokenlänge refers to the number of tokens used to represent a piece of text. In the field of natural language processing (NLP), text is often broken down into smaller units called tokens. These tokens can be words, sub-word units, or even characters, depending on the tokenization method used. The length of the token sequence, or tokenlänge, is a crucial factor in many NLP tasks and models.

Different NLP models have varying limitations on the maximum tokenlänge they can process. For instance, large language models (LLMs) often have a context window, which defines the maximum number of tokens they can consider at any given time. Exceeding this limit can lead to information loss or performance degradation. Understanding and managing tokenlänge is essential for efficient and effective use of these models.

Tokenlänge can also impact computational resources. Longer sequences require more memory and processing power, which can affect training times and inference speeds. Therefore, techniques like truncation, summarization, or more efficient tokenization strategies are employed to handle long texts within model constraints. The specific definition of a token and how it is counted can vary between different NLP libraries and models, so it is important to be aware of the tokenization scheme in use.