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wav2vec2-bertr[)zwav2vec2-conformerr[)wav2vec2_phonemeWav2Vec2PhonemeCTCTokenizerwhisperWhisperTokenizerxclipxglm XGLMTokenizer)xlm XLMTokenizerz xlm-robertazxlm-roberta-xlxlnetXLNetTokenizerxlstmxmodyosoctt|dd5}tj|cdddS#1swYyxYw)z*Loads a vocabulary file into a dictionary.rutf-8encodingN)openjsonload) vocab_filereaders f/mnt/e/genesis-system/.venv/lib/python3.12/site-packages/transformers/models/auto/tokenization_auto.py load_vocabrWSs1 j# 0!Fyy !!!s.7cg}t|dd5}|D]O}|j}|s|jdr(|jt |j Q ddd|S#1swY|SxYw)z Loads a merges file into a list.rMrNrO#N)rQstrip startswithappendtuplesplit) merges_filemergesrUlines rV load_mergesrbYsr F k3 13V 3D::BloomTokenizerBloomTokenizerFastr)rrr ministralrrr;rz.tokenization_mistral_common transformers.ztransformers.models__name__)rrrTOKENIZER_MAPPING_NAMESitemsr importlib import_modulegetattrAttributeErrorTOKENIZER_MAPPING_extra_contentvalueshasattr)rc module_nametokenizer_classmodule tokenizer main_modules rVtokenizer_class_from_namer{dsC==  ,,&z2211+J77((  )@(E(E(G $ _ j (3K@Krr"88"001OQ_`"001[M1BDYZ vz22 '55<<> 9j$ /: = )).9K{J'{J// "  s D DDpretrained_model_name_or_path cache_dirforce_downloadproxiestokenrevisionlocal_files_only subfolderc "|jd} t|t|||||||ddd|  } | tj diSt | | } t | d5} tj| } ddd|  d<| S#1swYxYw)aY Loads the tokenizer configuration from a pretrained model tokenizer configuration. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. - a path to a *directory* containing a configuration file saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force to (re-)download the configuration files and override the cached versions if they exist. proxies (`dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request. token (`str` or *bool*, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated when running `hf auth login` (stored in `~/.huggingface`). revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. local_files_only (`bool`, *optional*, defaults to `False`): If `True`, will only try to load the tokenizer configuration from local files. subfolder (`str`, *optional*, defaults to `""`): In case the tokenizer config is located inside a subfolder of the model repo on huggingface.co, you can specify the folder name here. Passing `token=True` is required when you want to use a private model. Returns: `dict`: The configuration of the tokenizer. Examples: ```python # Download configuration from huggingface.co and cache. tokenizer_config = get_tokenizer_config("google-bert/bert-base-uncased") # This model does not have a tokenizer config so the result will be an empty dict. tokenizer_config = get_tokenizer_config("FacebookAI/xlm-roberta-base") # Save a pretrained tokenizer locally and you can reload its config from transformers import AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-cased") tokenizer.save_pretrained("tokenizer-test") tokenizer_config = get_tokenizer_config("tokenizer-test") ``` _commit_hashF) r}r~rrrrr _raise_exceptions_for_gated_repo%_raise_exceptions_for_missing_entries'_raise_exceptions_for_connection_errorsrNz\Could not locate the tokenizer configuration file, will try to use the model config instead.rNrO) getrr loggerinfor rQrRrS) r|r}r~rrrrrkwargs commit_hashresolved_config_filerUresults rVget_tokenizer_configrsJ**^,K&%%))..305 # rs %&:KHK "W 5#6"#(F> M##s BBc\eZdZdZdZeeedee zfdZ e ddZ y) AutoTokenizera This is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when created with the [`AutoTokenizer.from_pretrained`] class method. This class cannot be instantiated directly using `__init__()` (throws an error). ctd)Nz}AutoTokenizer is designed to be instantiated using the `AutoTokenizer.from_pretrained(pretrained_model_name_or_path)` method.)OSError)selfs rV__init__zAutoTokenizer.__init__s _  rdc P |jdd}d|d<|jdd}|jdd}|jdd}|jd}|vtj|d} | ,td |d d j d tDd t | } | td| d| j |g|i|S|r3t||fi|} t| dd} tjd(i| }n| tj |fd|i|}|j} t|fi|}|jdd}d}d|vr4t|dt t"fr|d}n|djdd}||| }| dk7rxtj| dj%dd|j%ddk7r?t& t'j |g|i|St |j |g|i|Sd|vr|d|d<|r|j%dd}|du}t-|t.vxs%|duxrt |duxst |dzdu}|r:|d|d}n|d}d|vr|j1dd}nd}t3|||||}|rI|rGt5|fi|} |jdd}| j7| j |g|d|i|S|c|}t |} | |j9dst |dz} | | j:dk(rt&} | t&} | j |g|i|St=|ddrC|j>}d|vr|j%dd}t |} | j |g|i|St|t@rzt-|jBt-|jDurDt(jGd|jDjHd |jBjHd!|jD}tKt-|j:xs t=|d"d}|;t.jt-|t&} | | j |g|i|S|jdd}|o|d#k7r d|vr|dd$}t |} | |j9dst |dz} | | j:dk(rt&} | t&} | j |g|i|Std%|jHd&d j d't.Dd #t$rtj |fi|}YNwxYw#t$r#}t(j+d|Yd}~d}~wwxYw))a Instantiate one of the tokenizer classes of the library from a pretrained model vocabulary. The tokenizer class to instantiate is selected based on the `model_type` property of the config object (either passed as an argument or loaded from `pretrained_model_name_or_path` if possible), or when it's missing, by falling back to using pattern matching on `pretrained_model_name_or_path`: List options Params: pretrained_model_name_or_path (`str` or `os.PathLike`): Can be either: - A string, the *model id* of a predefined tokenizer hosted inside a model repo on huggingface.co. - A path to a *directory* containing vocabulary files required by the tokenizer, for instance saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. - A path or url to a single saved vocabulary file if and only if the tokenizer only requires a single vocabulary file (like Bert or XLNet), e.g.: `./my_model_directory/vocab.txt`. (Not applicable to all derived classes) inputs (additional positional arguments, *optional*): Will be passed along to the Tokenizer `__init__()` method. config ([`PreTrainedConfig`], *optional*) The configuration object used to determine the tokenizer class to instantiate. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force the (re-)download the model weights and configuration files and override the cached versions if they exist. proxies (`dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request. revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. subfolder (`str`, *optional*): In case the relevant files are located inside a subfolder of the model repo on huggingface.co (e.g. for facebook/rag-token-base), specify it here. tokenizer_type (`str`, *optional*): Tokenizer type to be loaded. backend (`str`, *optional*, defaults to `"tokenizers"`): Backend to use for tokenization. Valid options are: - `"tokenizers"`: Use the HuggingFace tokenizers library backend (default) - `"sentencepiece"`: Use the SentencePiece backend trust_remote_code (`bool`, *optional*, defaults to `False`): Whether or not to allow for custom models defined on the Hub in their own modeling files. This option should only be set to `True` for repositories you trust and in which you have read the code, as it will execute code present on the Hub on your local machine. kwargs (additional keyword arguments, *optional*): Will be passed to the Tokenizer `__init__()` method. Can be used to set special tokens like `bos_token`, `eos_token`, `unk_token`, `sep_token`, `pad_token`, `cls_token`, `mask_token`, `additional_special_tokens`. See parameters in the `__init__()` for more details. Examples: ```python >>> from transformers import AutoTokenizer >>> # Download vocabulary from huggingface.co and cache. >>> tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased") >>> # Download vocabulary from huggingface.co (user-uploaded) and cache. >>> tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-cased") >>> # If vocabulary files are in a directory (e.g. tokenizer was saved using *save_pretrained('./test/saved_model/')*) >>> # tokenizer = AutoTokenizer.from_pretrained("./test/bert_saved_model/") >>> # Download vocabulary from huggingface.co and define model-specific arguments >>> tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base", add_prefix_space=True) >>> # Explicitly use the tokenizers backend >>> tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer", backend="tokenizers") >>> # Explicitly use the sentencepiece backend >>> tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer", backend="sentencepiece") ```configNT _from_autouse_fasttokenizer_typetrust_remote_code gguf_filezPassed `tokenizer_type` z3 does not exist. `tokenizer_type` should be one of z, c3 K|]}|ywN.0cs rV z0AutoTokenizer.from_pretrained..`s Dq Ds rjzTokenizer class z is not currently imported.F)return_tensorsrwauto_maprFastz!Failed to use TokenizersBackend: rrrz-- code_revision PythonBackendPreTrainedTokenizerFastz The encoder model config class: z3 is different from the decoder model config class: z. It is not recommended to use the `AutoTokenizer.from_pretrained()` method in this case. Please use the encoder and decoder specific tokenizer classes. model_typerz!Unrecognized configuration class z8 to build an AutoTokenizer. Model type should be one of c34K|]}|jywr)rkrs rVrz0AutoTokenizer.from_pretrained..s4[AQZZ4[sr)&poprrl ValueErrorjoinr{from_pretrainedrr r for_model Exceptionrrr isinstancer]listreplacerrdebugtyperrr^r rregister_for_auto_classendswithrkrprwrdecoderencoderwarning __class__r)clsr|inputsrr_rrrtokenizer_class_namerw gguf_path config_dictconfig_model_typetokenizer_configtokenizer_config_classtokenizer_auto_mapehas_remote_codehas_local_code class_ref upstream_repotokenizer_class_candidate_classrs rVrzAutoTokenizer.from_pretrainedsdHd+#| JJz4 ($4d;"JJ':DAJJ{+   %#:#>#>~t#T #+ .~.>>qyy D,C DDEQH 88LMO& #34H3IId!eff2?223PdSYd]cd d #$A9WPVWI.yOPXYK))8K8F ^ c#331EVZ` #--00MXQWX!1!5!56G!N" ) )*:6 F%5j%A"%5j%A%E%EoW[%\"  &&2!-!R''++,=rBJJ6SUV%--fb9:!,J,<<=Zn]cngmnnU,-CDTT-06:@  - -%5n%EF> " !%;%C%CFB%O ",D8f):: "$ . )*@AMZ,-Cf-LMUYY  !!$0.q1 .q1 y ) 5a 8 $ 9!#@.Racp!  0;IGdohnoO ?D1A  3 3 52?22-06J[_e $ /(> %78QRO&/H/Q/QRX/Y";?22 ^^F/V 0E0EFm'RXZfhlJm  !/33DLBSTO*6667ThW]haghh"2!5!56G!N ! -%)<<KaAa)?)D&78NOO&/E/N/Nv/V";?s 1 1s @s jkpUUrrrr)NFNNNFr)>rrnrRos collectionsrtypingrtransformers.utils.import_utilsrconfiguration_utilsrdynamic_module_utilsrr modeling_gguf_pytorch_utilsr tokenization_utils_baser utilsr r rrr utils.hubrencoder_decoderr auto_factoryrconfiguration_autorrrrrtokenization_utils_tokenizersr tokenization_utils_sentencepiecer get_loggerrkrrdictstrr__annotations__rrlrrrmCONFIG_TO_TYPErWrbr{PathLikeboolrr__all__)kvs00rVrs #G3\?<%2*BH   H %68d3S >2702c49n-26+c3:o6K %<%>/DIK (?(A$tLK %<%>/DIK /F/H+dS K ,C,E(4P K $;$=4H K '>'@#dKK *A*C&NK (K $;$=4HK 9S9U5[_`K 3K *K +B+D'$OK 2I2K.QUVK &!K" 0G0I,tT#K$ 9%K& $;$=4H'K( &=&??TJ)K* ,+K, $;$=4H-K. "/K0 .E.G*TR1K2 &3K4 ,C,E4P5K6 %7K8 $;$=4H9K: '>'@OdK;K< "=K> /F/H+dS?K@ '>'@OdKAKB (?(A$tLCKD )@)B%MEKF )@)B%MGKH (?(A_tLIKJ "9";FKKL &MKN "OKP 3QKR .SKT $;$=4HUKV *A*C&NWKX /F/H+dSYKZ [K\ *A*CN]K^ 1H1J-PTU_K` '>'@OdKaKb $;$=4HcKd %<%>/DIeKf gKh /F/H+dSiKj !EXEZ"A`dekKl *mKn %<%>/DIoKp )@)BoMqKr )@)BoMsKt $;$=4HuKv "wKx (?(A$tLyKz &=&?"TJ{K| '>'@#dK}K~ '>'@#dKK@ ,C,E(4PAKB (?(A$tLCKD -D-F)DQEKF #:#<$GGKH '>'@#dKIKJ (?(A$tLKKL ,C,E(4PMKN 1H1J-PTUOKP )@)B%MQKR -D-F)DQSKT -D-F)DQUKV *A*C&NWKX ,C,E(4PYKZ )C)E%4P[K\ $;$=4H]K^ +B+D$O_K` '>'@OdKaKb +B+D'$OcKd :eKf $;$=4HgKh %iKj (kKl .mKn .oKp .E.G?TRqKr (?(A_tLsKt *A*C&NuKv +wKx &yKz (?(A$tL{K| )@)B%M}K~ ,C,E4PK@ 1H1JoPTUAKB )@)B%MCKD %<%>/DIEKF .E.G*TRGKH ,C,E(4PIKJ 0G0I,tTKKL (?(A_tLMKN 0G0I,tTOKP 0G0I,tTQKR .E.G*TRSKT "9";FUKV 0G0I,tTWKX '>'@#dKYKZ -D-F)DQ[K\ $;$==4H]K^ "_K` (?(A$tLaKb )C)E%4PcKd (?(A$tLeKf )@)B%MgKh (B(D$$OiKj ,C,E(4PkKl &=&?"TJmKn *A*C&NoKp %qKr -D-F/DQsKt 0G0I,tTuKv 'wKz *, #)@)B%  yKF *, #)@)B%  EKR *, #)@)B%  QK^ *, #)@)B%  ]Kh &@&B"MiKj 1H1JoPTUkKl 0G0I,tTmKn &=&?"TJoKp &=&?"TJqKr $sKt !8!: EuKv &=&?]TJwKx -D-FMDQyKz "9";F{K| "}K~ %<%>/DIK@ $;$=4HAKB (?(A_tLCKD (?(A$tLEKF /F/H+dSGKH '>'@#dKIKJ (?(A$tLKKL %<%>/DIMKN (?(A$tLOKP +B+D$OQKR )@)BoMSKT /F/H+dSUKV #:#<$GWKX &=&?"TJYKZ %<%>/DI[K\ &=&??TJ]K^ *A*C&N_K` ,C,E(4PaKb ,cKd #:#<$GeKf (gKh (?(A}tLiKl *, #)@)B%  kKv (?(A$tLwKx .yKz '>'@OdK{K| &=&?"TJ}K~ -D-F)DQK@ +B+D'$OAKB ,C,E(4PCKD *A*C&NEKF )@)B%MGKH &=&?"TJIKJ *A*C&NKKL .E.G*TRMKN *A*C&NOKP +B+D'$OQKR /F/H+dSSKT )@)B%MUKV -D-F)DQWKX YKZ %<%>/DI[K\ 0G0I,tT]K^ ,C,E(4P_K` *A*C&NaKb )@)BoMcKd (eKf 5gKh )iKj ,C,E(4PkKl '>'@#dKmKn $;$=4HoKp *A*CNqKr 3J3L/RVWsKt 6M6O2UYZuKv -D-F)DQwKx (B(D$$OyKz *A*C&N{K| 5O5Q1W[\}K~ ,F,H(dSK@ *AKB +B+D$OCKD +B+D'$OEKF *A*CNGKH 1H1J PTUIKJ  7 9}tDKKL (?(A$tLMKN $OKP +B+D'$OQKR #:#<$GSKT $;$=4HUKV "9";FWKX .YKZ 2[K\ $;$=4H]K^ +B+D$O_K` "aKd *, #)@)B%  cKp *, #)@)B%  oKz -{K| 2}K~ 7K@ /DIEKF $;$=4HGKH IKJ 1H1J-PTUKKL 4K4M0SWXMKN &=&?"TJOKP (?(A$tLQKR *A*C&NSKT &=&?"TJUKM^%%9;RS#=#7#=#=#?@41a!Q$@! )#)$s)d2B)\04 %)#"]#&S)9#9]R[[%%,]]#s(^d " ] #:  ] Dj ]]] #s(^]@cUcUL  0MAs n9