qi18ddlmZddlmZGddeZdgZy))PreTrainedConfig)RopeParameterscL eZdZdZdZddiZdgZ d-dedzdedzd edzd edzd ee dzd edzd edzdedzdedzde dzde dzdedzdedzdedzde dzdedzde dzde dzdedzde dzdedzdedzde dzdedzde dzd edzd!e dzd"e e e e fzdzd#e dzd$edzd%e dzd&edzd'edzd(edzd)edzd*e dzd+e dzfJfd, ZxZS). Zamba2Configa This is the configuration class to store the configuration of a [`Zamba2Model`]. It is used to instantiate a Zamba2 model according to the specified arguments, defining the model architecture. Instantiating a configuration with the defaults will yield a similar configuration to that of the Zamba2 model. [Zyphra/Zamba2-2.7B](https://huggingface.co/Zyphra/Zamba2-2.7B) Configuration objects inherit from [`PreTrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PreTrainedConfig`] for more information. Args: vocab_size (`int`, *optional*, defaults to 32000): Vocabulary size of the Zamba2 model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`Zamba2Model`] max_position_embeddings (`int`, *optional*, defaults to 4096): The maximum sequence length that this model might ever be used with. hidden_size (`int`, *optional*, defaults to 2560): Dimension of the hidden representations. num_hidden_layers (`int`, *optional*, defaults to 54): Number of hidden layers in the model. layers_block_type (`list`, *optional*): List of layer types, which can be either "mamba" or "hybrid". mamba_d_state (`int`, *optional*, defaults to 64): shape of the state space latents. mamba_d_conv (`int`, *optional*, defaults to 4): Size of the convolution kernel. mamba_expand (`int`, *optional*, defaults to 2): Expanding factor used to determine the intermediate size. mamba_ngroups (`int`, *optional*, defaults to 1): Number of groups for the evolution matrices of mamba 2. time_step_min (`float`, *optional*, defaults to 0.001): Minimum `time_step` used to bound `dt_proj.bias`. time_step_max (`float`, *optional*, defaults to 0.1): Maximum `time_step` used to bound `dt_proj.bias`. time_step_floor (`float`, *optional*, defaults to 0.0001): Minimum clamping value of the `dt_proj.bias` layer initialization. time_step_limit (`tuple`, *optional*): Accepted range of time step values. n_mamba_heads (`int`, *optional*, defaults to 8): Number of heads for the evolution matrices of mamba 2. use_conv_bias (`bool`, *optional*, defaults to `True`): Whether or not to use bias in the convolution layer of the mixer block. chunk_size (`int`, *optional*, defaults to 256): Size of the chunks that will comprise the sequence. use_mem_eff_path (`bool`, *optional*, defaults to `False`): Whether or not to use the fused conv1d and scan in mamba2 layers. add_bias_linear (`bool`, *optional*, defaults to `False`): Flag indicating whether or not to use bias in various layers intermediate_size (`int`, *optional*, defaults to 4 * hidden_size): Dimension of the MLP representations. hidden_act (`str`, *optional*, defaults to `"gelu"`): The non-linear activation function (function or string) in the MLP. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer in the Transformer decoder. num_key_value_heads (`int`, *optional*): This is the number of key_value heads that should be used to implement Grouped Query Attention. If `num_key_value_heads=None`, the model will use Multi Head Attention (MHA), if `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed by meanpooling all the original heads within that group. For more details, check out [this paper](https://huggingface.co/papers/2305.13245). attention_dropout (`float`, *optional*, defaults to 0.0): The dropout ratio for the attention probabilities. num_mem_blocks (`int`, *optional*, defaults to 1): Number of unshared transformer blocks. use_shared_attention_adapter (`bool`, *optional*, defaults to `False`): If True, unshared adapters (formally the same as LoRA but used in the base model) will be added to the q, k, v projectors in the shared attention layers. adapter_rank (`int`, *optional*, defaults to 128): Rank of the adapter in the shared MLP and shared attention layers. use_mem_rope (`bool`, *optional*, defaults to `False`): If True, includes RoPE in the shared attention layers. rope_parameters (`RopeParameters`, *optional*): Dictionary containing the configuration parameters for the RoPE embeddings. The dictionary should contain a value for `rope_theta` and optionally parameters used for scaling in case you want to use RoPE with longer `max_position_embeddings`. initializer_range (`float`, *optional*, defaults to 0.02): The standard deviation of the truncated_normal_initializer for initializing all weight matrices. rms_norm_eps (`float`, *optional*, defaults to 1e-05): The epsilon used by the rms normalization layers. use_cache (`bool`, *optional*, defaults to `True`): Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if `config.is_decoder=True`. num_logits_to_keep (`int` or `None`, *optional*, defaults to 1): Number of prompt logits to calculate during generation. If `None`, all logits will be calculated. If an integer value, only last `num_logits_to_keep` logits will be calculated. Default is 1 because only the logits of the last prompt token are needed for generation. For long sequences, the logits for the entire sequence may use a lot of memory so, setting `num_logits_to_keep=1` will reduce memory footprint significantly. pad_token_id (`int`, *optional*, defaults to 0): The id of the padding token. bos_token_id (`int`, *optional*, defaults to 1): The id of the "beginning-of-sequence" token. eos_token_id (`int`, *optional*, defaults to 2): The id of the "end-of-sequence" token. use_long_context (`bool`, *optional*, defaults to `False`): Activates the context-extended version of Zamba by modifying RoPE. tie_word_embeddings (`bool`, *optional*, defaults to `True`): Whether to tie weight embeddings ```python >>> from transformers import Zamba2Model, Zamba2Config >>> # Initializing a Zamba2-2.7B style configuration >>> configuration = Zamba2Config() >>> # Initializing a model from the Zamba2-2.7B style configuration >>> model = Zamba2Model(configuration) >>> # Accessing the model configuration >>> configuration = model.config ```zamba2head_dimattention_head_dimpast_key_valuesN vocab_sizemax_position_embeddings hidden_sizenum_hidden_layerslayers_block_type mamba_d_state mamba_d_conv mamba_expand mamba_ngroups time_step_min time_step_maxtime_step_floortime_step_limit n_mamba_heads use_conv_bias chunk_sizeuse_mem_eff_pathadd_bias_linearintermediate_size hidden_actnum_attention_headsnum_key_value_headsattention_dropoutnum_mem_blocksuse_shared_attention_adapter adapter_rank use_mem_roperope_parametersinitializer_range rms_norm_eps use_cachenum_logits_to_keep pad_token_id bos_token_id eos_token_iduse_long_contexttie_word_embeddingsc& *|!|_|"|_|#|_|%|_||_||_||_| d|z|_n||_||_||_ ||_ ||_ d|z|_ d|j z|jz|_ ||_||_|$|_||_||_||_||_||_| |_||_t1||z|z|_||_||_| |_||_||_| |_| |_ | |_!|$rd|_||}||_"||_ |j |jz|_#|j|_$|4dgdgdzdgzdzzdgdzzdgzdgdzzdgzdgdzz|_%n||_%||_&||_'||_(| |_)tU|jJD'(cgc] \}'}(|(dk(s |'c}(}'|_+||_,t[)|d i|&ycc}(}'w) Ni@mambahybridr)/r+r,r-r/r r r rrrrr"attention_hidden_sizer r!r%r.r&rrrrrrint mamba_headdimrrrr#r$rrrr kv_channelsnum_query_groupsrr'r(r)r* enumeratehybrid_layer_idsrsuper__init__)*selfr r r rrrrrrrrrrrrrrrrrrr r!r"r#r$r%r&r'r(r)r*r+r,r-r.r/kwargsindextype __class__s* a/opt/pipecat/venv/lib/python3.12/site-packages/transformers/models/zamba2/configuration_zamba2.pyr@zZamba2Config.__init__syR)((#6 $'>$&  $%&_D "%6D "$!2#6 ,%&_""#d&6&6"6$:R:R"R!2( 0.*((.**  !;< M*$.,H)(**. +0D (  &"5 #6 #6 ++t/G/GG $ 8 8  $ 9q=H:-23)a- *)a-  *  )a-    "&7D "!2(""4:CDDZDZ:[ p;5$_cgo_o p 0 "6"!qs  H+H)%i}ii 6N@r1r2gMbP?g?g-C6?NTFFNgelu NgrIFFNg{Gz?gh㈵>TrIrIr2FT)__name__ __module__ __qualname____doc__ model_type attribute_mapkeys_to_ignore_at_inferencer9liststrfloatboolrdictr@ __classcell__)rEs@rFrrsf PJ!56M#4"5"'.2"&(*.2$&#$#$$%&+&)&*&*$%%)!$(-',(,!'*,*.*-%&49#&$)MQ*.#'!%)*#$#$#$(-+/Mi#$Ji#"%ti#4Z i# : i#  9t+ i#Tzi#Dji#Dji#Tzi#t|i#t|i#ti#ti#Tzi# d{!i#"$J#i#$+%i#&'i#(:)i#*$J+i#,!4Z-i#.!4Z/i#0!4<1i#2d 3i#4'+Tk5i#6Dj7i#8Tk9i#:($sN/B*CCdJ;i#<!4<=i#>Dj?i#@$;Ai#B $JCi#DDjEi#FDjGi#HDjIi#J+Ki#L"D[Mi#i#rN)configuration_utilsrmodeling_rope_utilsrr__all__r7r]rFras'"41V##V#r  r]