tiktoken is a fast BPE tokeniser for use with OpenAI's models.

import tiktoken
enc = tiktoken.get_encoding("cl100k_base")
assert enc.decode(enc.encode("hello world")) == "hello world"

# To get the tokeniser corresponding to a specific model in the OpenAI API:
enc = tiktoken.encoding_for_model("gpt-4")

The open source version of tiktoken can be installed from PyPI:

pip install tiktoken

The tokeniser API is documented in tiktoken/core.py.

Example code using tiktoken can be found in the OpenAI Cookbook.

tiktoken is between 3-6x faster than a comparable open source tokeniser:

Performance measured on 1GB of text using the GPT-2 tokeniser, using GPT2TokenizerFast from tokenizers==0.13.2, transformers==4.24.0 and tiktoken==0.2.0.

Please post questions in the issue tracker.

If you work at OpenAI, make sure to check the internal documentation or feel free to contact @shantanu.

Language models don't see text like you and I, instead they see a sequence of numbers (known as tokens). Byte pair encoding (BPE) is a way of converting text into tokens. It has a couple desirable properties:

1. It's reversible and lossless, so you can convert tokens back into the original text
2. It works on arbitrary text, even text that is not in the tokeniser's training data
3. It compresses the text: the token sequence is shorter than the bytes corresponding to the orig