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vocab : add tokenizer support for jina-embeddings-v2-base-zh (#18756)

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* vocab : add jina-embeddings-v2-base-zh (whitespace tokenizer)

* lowercase defaults to true

* type fix

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
o7si 2026-05-31 18:37:35 +08:00 committed by GitHub
parent 3292da09f6
commit d4c8e2c29c
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9 changed files with 106 additions and 4 deletions
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10
conversion/base.py
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@ -1692,6 +1692,16 @@ class TextModel(ModelBase):
special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
special_vocab.add_to_gguf(self.gguf_writer)
def _set_vocab_whitespace(self) -> None:
tokens, toktypes, _ = self.get_vocab_base()
self.gguf_writer.add_tokenizer_model("whitespace")
self.gguf_writer.add_tokenizer_pre("whitespace") # pinned, not hash-detected: chktxt hash collides with jina-v1-en
self.gguf_writer.add_token_list(tokens)
self.gguf_writer.add_token_types(toktypes)
special_vocab = gguf.SpecialVocab(self.dir_model, load_merges=True)
special_vocab.add_to_gguf(self.gguf_writer)
def _set_vocab_hybriddna(self):
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained(self.dir_model, trust_remote_code=True)

11
conversion/bert.py
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@ -571,7 +571,16 @@ class JinaBertV2Model(BertModel):
if tokenizer_class == 'BertTokenizer':
super().set_vocab()
elif tokenizer_class == 'RobertaTokenizer':
self._set_vocab_gpt2()
pre_tokenizer_type = None
tokenizer_json_path = self.dir_model / "tokenizer.json"
if tokenizer_json_path.is_file():
with open(tokenizer_json_path, "r", encoding="utf-8") as f:
pre_tokenizer_type = json.load(f).get("pre_tokenizer", {}).get("type")
if pre_tokenizer_type == "Whitespace":
self._set_vocab_whitespace()
else:
self._set_vocab_gpt2()
self.gguf_writer.add_token_type_count(2)
else:
raise NotImplementedError(f'Tokenizer {tokenizer_class} is not supported for JinaBertModel')

2
gguf-py/gguf/constants.py
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@ -268,6 +268,8 @@ class Keys:
CHAT_TEMPLATE = "tokenizer.chat_template"
CHAT_TEMPLATE_N = "tokenizer.chat_template.{name}"
CHAT_TEMPLATES = "tokenizer.chat_templates"
# Normalizer constants
NORMALIZER_LOWERCASE = "tokenizer.ggml.normalizer.lowercase"
# FIM/Infill special tokens constants
FIM_PRE_ID = "tokenizer.ggml.fim_pre_token_id"
FIM_SUF_ID = "tokenizer.ggml.fim_suf_token_id"

3
gguf-py/gguf/gguf_writer.py
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@ -1110,6 +1110,9 @@ class GGUFWriter:
self.add_string(Keys.Tokenizer.CHAT_TEMPLATE, value)
def add_normalizer_lowercase(self, value: bool) -> None:
self.add_bool(Keys.Tokenizer.NORMALIZER_LOWERCASE, value)
def add_eot_token_id(self, id: int) -> None:
self.add_uint32(Keys.Tokenizer.EOT_ID, id)

27
gguf-py/gguf/vocab.py
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@ -52,6 +52,7 @@ class SpecialVocab:
add_special_token: dict[str, bool]
special_token_ids: dict[str, int]
chat_template: str | Sequence[Mapping[str, str]] | None
normalizer_lowercase: bool | None
def __init__(
self, path: str | os.PathLike[str], load_merges: bool = False,
@ -64,6 +65,7 @@ class SpecialVocab:
self.load_merges = load_merges
self.merges = []
self.chat_template = None
self.normalizer_lowercase = None
if special_token_types is not None:
self.special_token_types = special_token_types
else:
@ -102,6 +104,10 @@ class SpecialVocab:
if not quiet:
logger.info(f'Setting chat_template to {self.chat_template}')
gw.add_chat_template(self.chat_template)
if self.normalizer_lowercase is not None:
if not quiet:
logger.info(f'Setting normalizer_lowercase to {self.normalizer_lowercase}')
gw.add_normalizer_lowercase(self.normalizer_lowercase)
def _load(self, path: Path) -> None:
self._try_load_from_tokenizer_json(path)
@ -146,6 +152,24 @@ class SpecialVocab:
return
logger.warning(f'Special token type {typ}, id {tid} out of range, must be under {self.n_vocab} - skipping')
def _parse_normalizer(self, normalizer: dict) -> None:
# ref: https://huggingface.co/docs/tokenizers/api/normalizers
#
# Detects lowercase normalization in three possible formats:
# 1. Standalone: {"type": "Lowercase"}
# 2. BertNormalizer attribute: {"type": "BertNormalizer", "lowercase": true, ...}
# 3. Nested in Sequence: {"type": "Sequence", "normalizers": [...]}
normalizer_type = normalizer.get('type')
if normalizer_type == 'Lowercase':
self.normalizer_lowercase = True
elif normalizer_type == 'BertNormalizer':
if 'lowercase' in normalizer:
self.normalizer_lowercase = normalizer['lowercase']
elif normalizer_type == 'Sequence':
for norm in normalizer.get('normalizers', []):
self._parse_normalizer(norm)
def _try_load_from_tokenizer_json(self, path: Path) -> bool:
tokenizer = None
tokenizer_file = path / 'tokenizer.json'
@ -178,6 +202,9 @@ class SpecialVocab:
]
else:
raise ValueError("Unknown tokenizer merges format")
# Parse normalizer configuration (e.g. Lowercase) into metadata
if normalizer := tokenizer.get('normalizer'):
self._parse_normalizer(normalizer)
added_tokens = tokenizer.get('added_tokens', {})
else:
added_tokens = {}

1
src/llama-arch.cpp
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@ -319,6 +319,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
{ LLM_KV_TOKENIZER_HF_JSON, "tokenizer.huggingface.json" },
{ LLM_KV_TOKENIZER_RWKV, "tokenizer.rwkv.world" },
{ LLM_KV_TOKENIZER_CHAT_TEMPLATE, "tokenizer.chat_template" },
{ LLM_KV_TOKENIZER_NORMALIZER_LOWERCASE, "tokenizer.ggml.normalizer.lowercase" },
{ LLM_KV_TOKENIZER_FIM_PRE_ID, "tokenizer.ggml.fim_pre_token_id" },
{ LLM_KV_TOKENIZER_FIM_SUF_ID, "tokenizer.ggml.fim_suf_token_id" },
{ LLM_KV_TOKENIZER_FIM_MID_ID, "tokenizer.ggml.fim_mid_token_id" },

1
src/llama-arch.h
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@ -308,6 +308,7 @@ enum llm_kv {
LLM_KV_TOKENIZER_HF_JSON,
LLM_KV_TOKENIZER_RWKV,
LLM_KV_TOKENIZER_CHAT_TEMPLATE,
LLM_KV_TOKENIZER_NORMALIZER_LOWERCASE,
LLM_KV_TOKENIZER_FIM_PRE_ID,
LLM_KV_TOKENIZER_FIM_SUF_ID,
LLM_KV_TOKENIZER_FIM_MID_ID,

53
src/llama-vocab.cpp
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@ -519,6 +519,13 @@ struct llm_tokenizer_bpe : llm_tokenizer {
"(?:'[sS]|'[tT]|'[rR][eE]|'[vV][eE]|'[mM]|'[lL][lL]|'[dD])|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}+| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
};
break;
case LLAMA_VOCAB_PRE_TYPE_WHITESPACE:
// whitespace pre-tokenizer (jinaai/jina-embeddings-v2-base-zh)
regex_exprs = {
"\\S+",
};
byte_encode = false;
break;
default:
// default regex for BPE tokenization pre-processing
regex_exprs = {
@ -1671,6 +1678,35 @@ private:
const llama_vocab & vocab;
};
struct llm_tokenizer_whitespace_session : llm_tokenizer_bpe_session {
llm_tokenizer_whitespace_session(const llama_vocab & vocab, const llm_tokenizer_bpe & tokenizer) : llm_tokenizer_bpe_session{vocab, tokenizer}, vocab{vocab} {}
void tokenize(const std::string & text, std::vector<llama_token> & output) override {
const bool lowercase = vocab.get_normalizer_lowercase();
std::string segment;
auto flush = [&]() {
if (!segment.empty()) {
llm_tokenizer_bpe_session::tokenize(segment, output);
segment.clear();
}
};
for (uint32_t cpt : unicode_cpts_from_utf8(text)) {
// drop whitespace
if (unicode_cpt_flags_from_cpt(cpt).is_whitespace) {
flush();
} else {
segment += unicode_cpt_to_utf8(lowercase ? unicode_tolower(cpt) : cpt);
}
}
flush();
}
private:
const llama_vocab & vocab;
};
//
// impl
//
@ -1751,6 +1787,7 @@ struct llama_vocab::impl {
bool remove_extra_whitespaces = false;
bool escape_whitespaces = true;
bool treat_whitespace_as_suffix = false;
bool normalizer_lowercase = true; // Lowercase normalizer (tokenizer.json)
std::unordered_map<std::string, llama_token> token_to_id;
std::vector<token_data> id_to_token;
@ -1900,7 +1937,7 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
special_mask_id = 103;
add_sep = true;
} else if (tokenizer_model == "gpt2" || tokenizer_model == "hybriddna") {
} else if (tokenizer_model == "gpt2" || tokenizer_model == "hybriddna" || tokenizer_model == "whitespace") {
type = LLAMA_VOCAB_TYPE_BPE;
// read bpe merges and populate bpe ranks
@ -2119,6 +2156,9 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
tokenizer_pre == "roberta-bpe") {
pre_type = LLAMA_VOCAB_PRE_TYPE_GPT2;
add_sep = true;
} else if (
tokenizer_pre == "whitespace") {
pre_type = LLAMA_VOCAB_PRE_TYPE_WHITESPACE;
} else if (
tokenizer_pre == "refact") {
pre_type = LLAMA_VOCAB_PRE_TYPE_REFACT;
@ -2299,8 +2339,9 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
pre_type = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
}
ml.get_key(LLM_KV_TOKENIZER_ADD_PREFIX, add_space_prefix, false);
ml.get_key(LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, remove_extra_whitespaces, false);
ml.get_key(LLM_KV_TOKENIZER_ADD_PREFIX, add_space_prefix, false);
ml.get_key(LLM_KV_TOKENIZER_REMOVE_EXTRA_WS, remove_extra_whitespaces, false);
ml.get_key(LLM_KV_TOKENIZER_NORMALIZER_LOWERCASE, normalizer_lowercase, false);
}
const int token_idx = gguf_find_key(ctx, kv(LLM_KV_TOKENIZER_LIST).c_str());
@ -3264,6 +3305,8 @@ std::vector<llama_token> llama_vocab::impl::tokenize(
std::unique_ptr<llm_tokenizer_bpe_session> session;
if (vocab.get_tokenizer_model() == "hybriddna") {
session = std::make_unique<llm_tokenizer_hybriddna_session>(vocab, *tok_bpe);
} else if (vocab.get_tokenizer_model() == "whitespace") {
session = std::make_unique<llm_tokenizer_whitespace_session>(vocab, *tok_bpe);
} else {
session = std::make_unique<llm_tokenizer_bpe_session>(vocab, *tok_bpe);
}
@ -3892,6 +3935,10 @@ bool llama_vocab::get_treat_whitespace_as_suffix() const {
return pimpl->treat_whitespace_as_suffix;
}
bool llama_vocab::get_normalizer_lowercase() const {
return pimpl->normalizer_lowercase;
}
int llama_vocab::max_token_len() const {
return pimpl->max_token_len;
}

2
src/llama-vocab.h
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@ -61,6 +61,7 @@ enum llama_vocab_pre_type {
LLAMA_VOCAB_PRE_TYPE_GEMMA4 = 50,
LLAMA_VOCAB_PRE_TYPE_SARVAM_MOE = 51,
LLAMA_VOCAB_PRE_TYPE_MINICPM5 = 52,
LLAMA_VOCAB_PRE_TYPE_WHITESPACE = 53,
};
struct LLM_KV;
@ -138,6 +139,7 @@ struct llama_vocab {
bool get_remove_extra_whitespaces () const;
bool get_escape_whitespaces () const;
bool get_treat_whitespace_as_suffix() const;
bool get_normalizer_lowercase () const;
int max_token_len() const;