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wav2vec2-bertr[)zwav2vec2-conformerr[)wav2vec2_phonemeWav2Vec2PhonemeCTCTokenizerwhisperWhisperTokenizerxclipxglm XGLMTokenizer)xlm XLMTokenizerz xlm-robertazxlm-roberta-xlxlnetXLNetTokenizerxlstmxmodyoso>fuyuphi3jambajanusllavaarcticopencuastep3p5vipllava internlm2 llava_next deepseek_vldeepseek_vl_v2hyperclovax_vlmdeepseek_vl_hybrid)MODELS_WITH_INCORRECT_HUB_TOKENIZER_CLASSctt|dd5}tj|cdddS#1swYyxYw)z*Loads a vocabulary file into a dictionary.rutf-8encodingN)openjsonload) vocab_filereaders \/opt/pipecat/venv/lib/python3.12/site-packages/transformers/models/auto/tokenization_auto.py load_vocabrhqs1 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.r^r_r`#N)rbstrip startswithappendtuplesplit) merges_filemergesrflines rg load_mergesrswsr F k3 13V 3D::BloomTokenizerBloomTokenizerFastr)rrrrrrr<rz.tokenization_mistral_common transformers.ztransformers.models__name__)rrrTOKENIZER_MAPPING_NAMESitemsr importlib import_modulegetattrAttributeErrorTOKENIZER_MAPPING_extra_contentvalueshasattr)rt module_nametokenizer_classmodule tokenizer main_modules rgtokenizer_class_from_namersC==  ,,&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) rrrrrrr _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.r_r`) getrr loggerinfor rbrcrd) rrrrrrrrkwargs commit_hashresolved_config_filerfresults rgget_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 rg__init__zAutoTokenizer.__init__s _  ruc  |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}||| | dk7rtj| wtj| j%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 | t0vrd}d}|r:|d|d}n|d}d|vr|j3dd}nd}t5|||||}|rI|rGt7|fi|} |jdd}| j9| j |g|d|i|S|c|}t |} | |j;dst |dz} | | j<dk(rt&} | t&} | j |g|i|St?|ddrC|j@}d|vr|j%dd}t |} | j |g|i|St|tBrzt-|jDt-|jFurDt(jId|jFjJd |jDjJd!|jF}tMt-|j<xs t?|d"d}|;t.jt-|t&} | | j |g|i|S|jdd}|o|d#k7r d|vr|dd$}t |} | |j;dst |dz} | | j<dk(rt&} | t&} | j |g|i|Std%|jJd&d j d't.Dd #t$rtj |fi|}YpwxYw#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 rg z0AutoTokenizer.from_pretrained..~s Dq Ds rzzTokenizer class z is not currently imported.F)return_tensorsrauto_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)r{rs rgrz0AutoTokenizer.from_pretrained..s4[AQZZ4[sr)'poprr| ValueErrorjoinrfrom_pretrainedrr r for_model Exceptionrrr isinstancernlistreplacerrdebugtyperr\ror rregister_for_auto_classendswithr{rrrdecoderencoderwarning __class__r)clsrinputsrr_rrrtokenizer_class_namer gguf_path config_dictconfig_model_typetokenizer_configtokenizer_config_classtokenizer_auto_mapehas_remote_codehas_local_code class_ref upstream_repotokenizer_class_candidate_classrs rgrzAutoTokenizer.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''++,=>J'++,=>FFvrR%--fb9:!,J,<<=Zn]cngmnnU,-CDTT-06:@  - -%5n%EF> " !%;%C%CFB%O ",D8f):: "$ . )*@AMZ,-Cf-LMUYY  04]]#O!%  !!$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";?z 1 1z @z xkpUUrrr)NFNNNFr)Arr~rcos 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_loggerr{rrdictstrr__annotations__rr|r\setrrr}CONFIG_TO_TYPErhrsrPathLikeboolrr__all__)kvs00rgrs% #G3\?<%2*BH   H %68d3S >2702c49n-26+c3:o6Q %<%>/DIQ (?(A$tLQ %<%>/DIQ /F/H+dS Q ,C,E(4P Q $;$=4H Q '>'@#dKQ *A*C&NQ (Q $;$=4HQ 9S9U5[_`Q 3Q *Q +B+D'$OQ 2I2K.QUVQ &!Q" 0G0I,tT#Q$ 9%Q& $;$=4H'Q( &=&??TJ)Q* ,+Q, $;$=4H-Q. "/Q0 .E.G*TR1Q2 &3Q4 ,C,E4P5Q6 %7Q8 $;$=4H9Q: '>'@OdK;Q< "=Q> /F/H+dS?Q@ '>'@OdKAQB (?(A$tLCQD )@)B%MEQF )@)B%MGQH (?(A_tLIQJ "9";FKQL &MQN "OQP 3QQR .SQT $;$=4HUQV *A*C&NWQX /F/H+dSYQZ [Q\ *A*CN]Q^ 1H1J-PTU_Q` '>'@OdKaQb $;$=4HcQd %<%>/DIeQf gQh /F/H+dSiQj !EXEZ"A`dekQl *mQn %<%>/DIoQp )@)BoMqQr )@)BoMsQt $;$=4HuQv "wQx (?(A$tLyQz &=&?"TJ{Q| '>'@#dK}Q~ '>'@#dKQ@ ,C,E(4PAQB (?(A$tLCQD -D-F)DQEQF #:#<$GGQH '>'@#dKIQJ (?(A$tLKQL ,C,E(4PMQN 1H1J-PTUOQP )@)B%MQQR -D-F)DQSQT -D-F)DQUQV *A*C&NWQX ,C,E(4PYQZ )C)E%4P[Q\ $;$=4H]Q^ +B+D$O_Q` '>'@OdKaQb +B+D'$OcQd :eQf $;$=4HgQh %iQj (kQl .mQn .oQp .E.G?TRqQr (?(A_tLsQt *A*C&NuQv +wQx &yQz (?(A$tL{Q| )@)B%M}Q~ ,C,E4PQ@ 1H1JoPTUAQB )@)B%MCQD %<%>/DIEQF .E.G*TRGQH ,C,E(4PIQJ 0G0I,tTKQL (?(A_tLMQN 0G0I,tTOQP 0G0I,tTQQR .E.G*TRSQT "9";FUQV 0G0I,tTWQX '>'@#dKYQZ -D-F)DQ[Q\ "]Q^ (?(A$tL_Q` )C)E%4PaQb (?(A$tLcQd )@)B%MeQf (B(D$$OgQh ,C,E(4PiQj &=&?"TJkQl *A*C&NmQn %oQp -D-F/DQqQr 0G0I,tTsQt 'uQx *, #)@)B%  wQD *, #)@)B%  CQP *, #)@)B%  OQ\ *, #)@)B%  [Qh *, #)@)B%  gQr &@&B"MsQt 1H1JoPTUuQv 0G0I,tTwQx &=&?"TJyQz &=&?"TJ{Q| $}Q~ !8!: EQ@ &=&?]TJAQB -D-FMDQCQD "9";FEQF "GQH %<%>/DIIQJ $;$=4HKQL (?(A_tLMQN (?(A$tLOQP /F/H+dSQQR '>'@#dKSQT (?(A$tLUQV )@)B%MWQX /F/H+dSYQZ (?(A$tL[Q\ +B+D$O]Q^ )@)BoM_Q` /F/H+dSaQb #:#<$GcQd &=&?"TJeQf %<%>/DIgQh &=&??TJiQj *A*C&NkQl ,C,E(4PmQn ,oQp #:#<$GqQr (sQt (?(A}tLuQx *, #)@)B%  wQB (?(A$tLCQD .EQF '>'@OdKGQH &=&?"TJIQJ -D-F)DQKQL +B+D'$OMQN ,C,E(4POQP *A*C&NQQR )@)B%MSQT &=&?"TJUQV *A*C&NWQX .E.G*TRYQZ *A*C&N[Q\ +B+D'$O]Q^ /F/H+dS_Q` )@)B%MaQb -D-F)DQcQd eQf %<%>/DIgQh 0G0I,tTiQj ,C,E(4PkQl *A*C&NmQn )@)BoMoQp (qQr 5sQt )uQv ,C,E(4PwQx '>'@#dKyQz $;$=4H{Q| *A*CN}Q~ 3J3L/RVWQ@ 6M6O2UYZAQB -D-F)DQCQD (B(D$$OEQF *A*C&NGQH 5O5Q1W[\IQJ ,F,H(dSKQL *MQN +B+D$OOQP +B+D'$OQQR *A*CNSQT 1H1J PTUUQV  7 9}tDWQX (?(A$tLYQZ $[Q\ +B+D'$O]Q^ #:#<$G_Q` $;$=4HaQb "9";FcQd .eQf 2gQh $;$=4HiQj +B+D$OkQl "mQp *, #)@)B%  oQ| *, #)@)B%  {QF -GQH 2IQJ 7KQL /DIQQR $;$=4HSQT UQV 1H1J-PTUWQX 4K4M0SWXYQZ &=&?"TJ[Q\ (?(A$tL]Q^ *A*C&N_Q` &=&?"TJaQSn7)3s8$<iJ00E\E^.Adh +i%%9;RS#=#7#=#=#?@41a!Q$@! )#)$s)d2B)\04 %)#"]#&S)9#9]R[[%%,]]#s(^d " ] #:  ] Dj ]]] #s(^]@jUjUZ  0[As o8