Bundle of more than 30 new text objects for Neovim.
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Updated
Aug 3, 2026 - Lua
Bundle of more than 30 new text objects for Neovim.
Korean text normalization and language preparation package for LM in Kaldi-based ASR system
Simple-to-use scoring function for arbitrarily tokenized texts.
Keyword Search Recipe for Subword ASR
Subword-augmented Embedding for Cloze Reading Comprehension (COLING 2018)
johnny - a neural network graph based DEPendency Parser
Effective Subword Segmentation for Text Comprehension (TASLP 2019)
Unsupervised Word Segmentation using Minimum Description Length for Neural Machine Translation (NMT)
A causal intervention framework to learn robust and interpretable character representations inside subword-based language models
An implementation of subword division algorithm proposed in T. Mikolov (2012).
A framework for generating subword vocabulary from a tensorflow dataset and building custom BERT tokenizer models.
This repository contains source code implementation of assignments for NTU's MSAI course AI6127 on Deep Neural Networks for Natural Language Processing (2019 Sem 2).
A subword-level GRU language model inference engine.
🧠 Build and explore a minimal Byte Pair Encoding tokenizer in TypeScript, training and encoding text using raw UTF-8 bytes without external libraries.
Tokenization is a way of separating a piece of text into smaller units called tokens. Here, tokens can be either words, characters, or subwords. Hence, tokenization can be broadly classified into 3 types – word, character, and subword (n-gram characters) tokenization.
Subword Neural Machine Translation
Com la tokenització fractura la morfologia catalana i si una segmentació conscient dels morfemes recupera la geometria. Provat en 3 llengües indoeuropees (català, castellà, anglès): el català es fragmenta ~1,7× més que l'anglès; forçar el tall morfèmic recupera la composicionalitat (robust a portadora i replicat en castellà).
200k-vocab SentencePiece (Unigram) tokenizer for German-primary LLMs — German/English/code, low fertility, byte-fallback, chat-template tokens. From the Auralis/Helix project.
Byte-pair encoding (BPE) subword tokenizer in pure Standard ML: train, encode, decode. Deterministic, MLton + Poly/ML.
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