SCALING_FINETUNED = "{arch}.rope.scaling.finetuned"
class Tokenizer:
- MODEL = "tokenizer.ggml.model"
- LIST = "tokenizer.ggml.tokens"
- TOKEN_TYPE = "tokenizer.ggml.token_type"
- SCORES = "tokenizer.ggml.scores"
- MERGES = "tokenizer.ggml.merges"
- BOS_ID = "tokenizer.ggml.bos_token_id"
- EOS_ID = "tokenizer.ggml.eos_token_id"
- UNK_ID = "tokenizer.ggml.unknown_token_id"
- SEP_ID = "tokenizer.ggml.seperator_token_id"
- PAD_ID = "tokenizer.ggml.padding_token_id"
- ADD_BOS = "tokenizer.ggml.add_bos_token"
- ADD_EOS = "tokenizer.ggml.add_eos_token"
- HF_JSON = "tokenizer.huggingface.json"
- RWKV = "tokenizer.rwkv.world"
+ MODEL = "tokenizer.ggml.model"
+ LIST = "tokenizer.ggml.tokens"
+ TOKEN_TYPE = "tokenizer.ggml.token_type"
+ SCORES = "tokenizer.ggml.scores"
+ MERGES = "tokenizer.ggml.merges"
+ BOS_ID = "tokenizer.ggml.bos_token_id"
+ EOS_ID = "tokenizer.ggml.eos_token_id"
+ UNK_ID = "tokenizer.ggml.unknown_token_id"
+ SEP_ID = "tokenizer.ggml.seperator_token_id"
+ PAD_ID = "tokenizer.ggml.padding_token_id"
+ ADD_BOS = "tokenizer.ggml.add_bos_token"
+ ADD_EOS = "tokenizer.ggml.add_eos_token"
+ HF_JSON = "tokenizer.huggingface.json"
+ RWKV = "tokenizer.rwkv.world"
+ CHAT_TEMPLATE = "tokenizer.chat_template"
#
def add_add_eos_token(self, value: bool) -> None:
self.add_bool(Keys.Tokenizer.ADD_EOS, value)
+ def add_chat_template(self, value: str) -> None:
+ self.add_string(Keys.Tokenizer.CHAT_TEMPLATE, value)
+
def _pack(self, fmt: str, value: Any, skip_pack_prefix: bool = False) -> bytes:
pack_prefix = ''
if not skip_pack_prefix:
merges: list[str]
add_special_token: dict[str, bool]
special_token_ids: dict[str, int]
+ chat_template: str | None
def __init__(
self, path: str | os.PathLike[str], load_merges: bool = False,
self.n_vocab = n_vocab
self.load_merges = load_merges
self.merges = []
+ self.chat_template = None
if special_token_types is not None:
self.special_token_types = special_token_types
else:
if not quiet:
print(f'gguf: Setting add_{typ}_token to {value}')
add_handler(value)
+ if self.chat_template is not None:
+ if not quiet:
+ print(f'gguf: Setting chat_template to {self.chat_template}')
+ gw.add_chat_template(self.chat_template)
def _load(self, path: Path) -> None:
self._try_load_from_tokenizer_json(path)
return True
with open(tokenizer_config_file, encoding = 'utf-8') as f:
tokenizer_config = json.load(f)
+ chat_template = tokenizer_config.get('chat_template')
+ if chat_template is None or isinstance(chat_template, str):
+ self.chat_template = chat_template
+ else:
+ print(
+ f'gguf: WARNING: Bad type for chat_template field in {tokenizer_config_file!r} - ignoring',
+ file = sys.stderr
+ )
for typ in self.special_token_types:
add_entry = tokenizer_config.get(f'add_{typ}_token')
if isinstance(add_entry, bool):
[tool.poetry]
name = "gguf"
-version = "0.5.3"
+version = "0.6.0"
description = "Read and write ML models in GGUF for GGML"
authors = ["GGML <ggml@ggml.ai>"]
packages = [
if (value.size() > MAX_VALUE_LEN) {
value = format("%s...", value.substr(0, MAX_VALUE_LEN - 3).c_str());
}
+ replace_all(value, "\n", "\\n");
LLAMA_LOG_INFO("%s: - kv %3d: %42s %-16s = %s\n", __func__, i, name, type_name.c_str(), value.c_str());
}