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                  " \5      r " S S\5      rS/r	g)zCPMAnt model configuration   )PretrainedConfig)loggingc                      ^  \ rS rSrSrSr               SS\S\S\S\S\S	\S
\S\S\S\S\S\S\S\S\4U 4S jjjr	Sr
U =r$ )CpmAntConfig   a
  
This is the configuration class to store the configuration of a [`CpmAntModel`]. It is used to instantiate an
CPMAnt 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 CPMAnt
[openbmb/cpm-ant-10b](https://huggingface.co/openbmb/cpm-ant-10b) architecture.

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 30720):
        Vocabulary size of the CPMAnt model. Defines the number of different tokens that can be represented by the
        `input` passed when calling [`CpmAntModel`].
    hidden_size (`int`, *optional*, defaults to 4096):
        Dimension of the encoder layers.
    num_attention_heads (`int`, *optional*, defaults to 32):
        Number of attention heads in the Transformer encoder.
    dim_head (`int`, *optional*, defaults to 128):
        Dimension of attention heads for each attention layer in the Transformer encoder.
    dim_ff (`int`, *optional*, defaults to 10240):
        Dimension of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
    num_hidden_layers (`int`, *optional*, defaults to 48):
        Number of layers of the Transformer encoder.
    dropout_p (`float`, *optional*, defaults to 0.0):
        The dropout probability for all fully connected layers in the embeddings, encoder.
    position_bias_num_buckets (`int`, *optional*, defaults to 512):
        The number of position_bias buckets.
    position_bias_max_distance (`int`, *optional*, defaults to 2048):
        The maximum sequence length that this model might ever be used with. Typically set this to something large
        just in case (e.g., 512 or 1024 or 2048).
    eps (`float`, *optional*, defaults to 1e-06):
        The epsilon used by the layer normalization layers.
    init_std (`float`, *optional*, defaults to 1.0):
        Initialize parameters with std = init_std.
    prompt_types (`int`, *optional*, defaults to 32):
        The type of prompt.
    prompt_length (`int`, *optional*, defaults to 32):
        The length of prompt.
    segment_types (`int`, *optional*, defaults to 32):
        The type of segment.
    use_cache (`bool`, *optional*, defaults to `True`):
        Whether to use cache.

Example:

```python
>>> from transformers import CpmAntModel, CpmAntConfig

>>> # Initializing a CPMAnt cpm-ant-10b style configuration
>>> configuration = CpmAntConfig()

>>> # Initializing a model from the cpm-ant-10b style configuration
>>> model = CpmAntModel(configuration)

>>> # Accessing the model configuration
>>> configuration = model.config
```cpmant
vocab_sizehidden_sizenum_attention_headsdim_headdim_ffnum_hidden_layers	dropout_pposition_bias_num_bucketsposition_bias_max_distanceepsinit_stdprompt_typesprompt_lengthsegment_types	use_cachec                    > [         TU ]  " S0 UD6  Xl        Xl        Xl        X l        X0l        X@l        XPl        X`l	        Xl
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   r   r   r   r   r   r   r   r   r   r	   r   )selfr	   r
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__module____qualname____firstlineno____doc__
model_typeintfloatboolr   __static_attributes____classcell__)r   s   @r   r   r      s    8t J  #%!#),*.!"!"! "! !	"!
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