Encode text with a Unigram tokenizer
Description
Normalizes (strip-right, multi-space collapse, control whitespace to
space), applies the Metaspace pre-tokenizer, segments each pre-token
by Viterbi over the Unigram scores, fuses consecutive unknowns, and
appends EOS. T5 semantics: right padding with <pad> (id 0),
truncation to max_length - 1 before the EOS.
Usage
encode_unigram(tokenizer, texts, max_length = 256L, add_eos = TRUE, pad = TRUE)
Arguments
tokenizer: Aunigram_tokenizer.texts: Character vector of prompts.max_length: Integer. Fixed sequence length (NULL for no truncation/padding).add_eos: Logical. Append the EOS token.pad: Logical. Right-pad tomax_length.
Value
List with input_ids and attention_mask, each an
integer matrix [length(texts), max_length] (or ragged lists when
max_length is NULL). Ids are 0-based (HuggingFace
convention); add 1 for R torch embedding lookups.