The tokenizer library is undergoing a major update to bitstream-based encoding and decoding methods, with a focus on improving performance and efficiency. This update aims to make tokenization a more significant component in ML workflows, potentially accelerating or decelerating machine learning processes.
Results What V1 Is The Split: Bitstreams Instead Of A Regex The Word Cache The Merge Loop Method What This Adds Up To Getting It Progress Towards V1 Release Candidate: Implemented 1.0.0 After 1.0.0 The tokenizer has not historically been the bottleneck within ML workflows. Compu…
This is why we have chosen to heavily focus on performance for the upcoming version 1 of tokenizers. Tokenization should be light and should scale with your workflow.
