ZjEdSrSSKJr SSKJr SSKJr \"SS9\"SS \555rS /rg ) zFlaubert configuration)strict)PreTrainedConfig)auto_docstringzflaubert/flaubert_base_uncased) checkpointct\rSrSr%SrSrSSSSSS S S .rS r\\ S 'Sr \ \ -\ S'Sr \ \ S'Sr\ \ S'Sr\ \ S'Sr\ \ S'Sr\ \ -\ S'Sr\ \ -\ S'Sr\\ S'S r\\ S'S r\\ S'S r\\ S'Sr\ \ S'Sr\\ S'Sr\ \ S 'S!r\ \ S"'S#r\ \ S$'S%r\ \ S&'S'r\ \ S('Sr\ \ S)'S*r\ \ S+'S,r \ \ S-'S.r!\ \ S/'Sr"\\ S0'S1r#\$\ S2'Sr%\\ S3'S4r&\$S4-\ S5'Sr'\\ S6'Sr(\ \ -\ S7'S.r)\ \ S8'S.r*\ \ S9'S'r+\ \ S:'S'r,\ \ S;'S*r-\ S4-\ S 'S'r.\ S4-\ S'Sr/\ \0\ -S4-\ S 'Sr1\\ S<'S=r2g4)>FlaubertConfiga pre_norm (`bool`, *optional*, defaults to `False`): Whether to apply the layer normalization before or after the feed forward layer following the attention in each layer (Vaswani et al., Tensor2Tensor for Neural Machine Translation. 2018) emb_dim (`int`, *optional*, defaults to 2048): The dimensionality of embedding layer. gelu_activation (`bool`, *optional*, defaults to True): Whether to use GeLU activation function. sinusoidal_embeddings (`bool`, *optional*, defaults to `False`): Whether or not to use sinusoidal positional embeddings instead of absolute positional embeddings. causal (`bool`, *optional*, defaults to `False`): Whether or not the model should behave in a causal manner. Causal models use a triangular attention mask in order to only attend to the left-side context instead if a bidirectional context. asm (`bool`, *optional*, defaults to `False`): Whether or not to use an adaptive log softmax projection layer instead of a linear layer for the prediction layer. n_langs (`int`, *optional*, defaults to 1): The number of languages the model handles. Set to 1 for monolingual models. use_lang_emb (`bool`, *optional*, defaults to `True`) Whether to use language embeddings. Some models use additional language embeddings, see [the multilingual models page](http://huggingface.co/transformers/multilingual.html#xlm-language-embeddings) for information on how to use them. embed_init_std (`float`, *optional*, defaults to 2048^-0.5): The standard deviation of the truncated_normal_initializer for initializing the embedding matrices. embed_init_std (`float`, *optional*, defaults to `2048**-0.5`): Initializer std for embedding layers. bos_index (`int`, *optional*, defaults to 0): The index of the beginning of sentence token in the vocabulary. eos_index (`int`, *optional*, defaults to 1): The index of the end of sentence token in the vocabulary. pad_index (`int`, *optional*, defaults to 2): The index of the padding token in the vocabulary. unk_index (`int`, *optional*, defaults to 3): The index of the unknown token in the vocabulary. mask_index (`int`, *optional*, defaults to 5): The index of the masking token in the vocabulary. is_encoder (`bool`, *optional*, defaults to True): Whether the model is used as an encoder. summary_type (`string`, *optional*, defaults to "first"): Argument used when doing sequence summary. Used in the sequence classification and multiple choice models. Has to be one of the following options: - `"last"`: Take the last token hidden state (like XLNet). - `"first"`: Take the first token hidden state (like BERT). - `"mean"`: Take the mean of all tokens hidden states. - `"cls_index"`: Supply a Tensor of classification token position (like GPT/GPT-2). - `"attn"`: Not implemented now, use multi-head attention. summary_use_proj (`bool`, *optional*, defaults to `True`): Argument used when doing sequence summary. Used in the sequence classification and multiple choice models. Whether or not to add a projection after the vector extraction. summary_activation (`str`, *optional*): Argument used when doing sequence summary. Used in the sequence classification and multiple choice models. Pass `"tanh"` for a tanh activation to the output, any other value will result in no activation. summary_proj_to_labels (`bool`, *optional*, defaults to `True`): Used in the sequence classification and multiple choice models. Whether the projection outputs should have `config.num_labels` or `config.hidden_size` classes. summary_first_dropout (`float`, *optional*, defaults to 0.1): Used in the sequence classification and multiple choice models. The dropout ratio to be used after the projection and activation. start_n_top (`int`, *optional*, defaults to 5): Used in the SQuAD evaluation script. end_n_top (`int`, *optional*, defaults to 5): Used in the SQuAD evaluation script. mask_token_id (`int`, *optional*, defaults to 0): Model agnostic parameter to identify masked tokens when generating text in an MLM context. lang_id (`int`, *optional*, defaults to 1): The ID of the language used by the model. This parameter is used when generating text in a given language. flaubertemb_dimn_headsn_layers vocab_size bos_token_id eos_token_id pad_token_id) hidden_sizenum_attention_headsnum_hidden_layersn_words bos_index eos_index pad_indexFpre_normg layerdropiui g?dropoutattention_dropoutTgelu_activationsinusoidal_embeddingscausalasmn_langs use_lang_embimax_position_embeddingsg;f?embed_init_stdg-q=layer_norm_epsg{Gz?init_stdrrrrr unk_index mask_index is_encoderfirst summary_typesummary_use_projNsummary_activationsummary_proj_to_labelssummary_first_dropout start_n_top end_n_top mask_token_idlang_idtie_word_embeddings)3__name__ __module__ __qualname____firstlineno____doc__ model_type attribute_maprbool__annotations__rfloatintrr rr rrr r!r"r#r%r&r'r(r)r*rrrr,r.r/r1strr2r3r4r5r6r7r8r9rrrlistr:__static_attributes__r;ڄ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/flaubert/configuration_flaubert.pyr r sBHJ ('###MHd Ius{ JGSHcGSGUS[%(us{( OT "'4'FDCGSL$#&S&&NE&!NE!HeIsIsIsIsJJL#!d!%)d )#'D'),53;,KIsM3GS L#*  L#* +,L#S /D(, $$rJr N) r@huggingface_hub.dataclassesrconfiguration_utilsrutilsrr __all__r;rJrKrPsK.3#;<t%%t%=t%n  rJ