+ KV-jJ^RIHt^RIHtHtHt^RIt^RIHtRRRlltR#))copy)ListOptionalUnionN) LLTokenizerc V^8dQhR\PR\\,R\\\\ \,3,,R\\ \ ,,R\/#) hf_tokenizern_vocab eos_tokenslicesreturn) transformersPreTrainedTokenizerFastrintrrstrr)formats"^/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/llguidance/hf.py __annotate__r s_&?&?66&? c]&?c49n-.&? T#Y  &?  &?c\V\P4'dc\VP4pVP 4VP 4VP4pVf VPp\WQW#R7#\R4h)a5 Create a new tokenizer from a fast Hugging Face tokenizer. This is an expensive operation (~1s), so the result should be cached. It currently only supports fast tokenizers, which are then handled by the Rust tokenizers library. Args: hf_tokenizer: transformers.PreTrainedTokenizerFast - the tokenizer to wrap n_vocab: int - override the size of the vocabulary eos_token: int or list of ints - override the EOS token(s) slices: List[str] - configuration for slicer optimization; pass [] to disable, or None to use the default configuration )r r r z"Only fast tokenizers are supported) isinstancerrrbackend_tokenizer no_padding no_truncationto_str eos_token_idr ValueError)r r r r rss&&&& rfrom_tokenizerr s(, D DEE!  * *  $$&'')  $ $ &  $11I1RR=>>r)NNN) rtypingrrrr_librr rrr$s((&?&?r