9i3XSrSSKJr SSKJr \R "5r"SS\5rg)zChatGLM model configuration )PretrainedConfig)loggercV^\rSrSrSrSrSU4SjjrSrU=r$) ChatGLMConfig a2 This is the configuration class to store the configuration of a [`~ChatGLMModel`]. It is used to instantiate an ChatGLM 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 ChatGLM-6B [THUDM/ChatGLM-6B](https://huggingface.co/THUDM/chatglm-6b) 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 150528): Vocabulary size of the ChatGLM-6B model. Defines the number of different tokens that can be represented by the `inputs_ids` passed when calling [`~ChatGLMModel`] or [`~TFChatGLMModel`]. hidden_size (`int`, *optional*, defaults to 4096): Dimension of the encoder layers and the pooler layer. num_hidden_layers (`int`, *optional*, defaults to 28): Number of hidden layers in the Transformer encoder. num_attention_heads (`int`, *optional*, defaults to 32): Number of attention heads for each attention layer in the Transformer encoder. inner_hidden_size (`int`, *optional*, defaults to 16384): Dimension of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. max_sequence_length (`int`, *optional*, defaults to 512): 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). layernorm_epsilon (`float`, *optional*, defaults to 1e-5): The epsilon used by the layer normalization layers. use_cache (`bool`, *optional*, defaults to `True`): Whether the model should return the last key/values attentions (not used by all models). Example: ```python >>> from modelscope.models.nlp.chatglm.configuration import ChatGLMConfig >>> from modelscope.models.nlp.chatglm.text_generation import ChatGLMModel >>> # Initializing a ChatGLM-6B THUDM/ChatGLM-6B style configuration >>> configuration = ChatGLMConfig() >>> # Initializing a model from the THUDM/ChatGLM-6B style configuration >>> model = ChatGLMModel(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` chatglmc >X0lXlX lX@lXlXPlXlX`lXplXl Xl Xl Xl Xl XlUUlUUl["TU]H"SU UUS.UD6 g)N) pad_token_id bos_token_id eos_token_id) num_layers vocab_size hidden_sizenum_attention_headsmax_sequence_lengthlayernorm_epsiloninner_hidden_size use_cacher r r mask_token_idgmask_token_idposition_encoding_2dquantization_bit pre_seq_lenprefix_projectionsuper__init__)selfrrrrrrr r rrr rrrrrrkwargs __class__s k/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/modelscope/models/nlp/chatglm/configuration.pyrChatGLMConfig.__init__=s&%$&#6 #6 !2!2"(((*,$8! 0&!2  %%%   )r r rrrrrrrrr rrrrrr)iLi gh㈵>FiIiIiIiIrii@TrNF) __name__ __module__ __qualname____firstlineno____doc__ model_typer__static_attributes__ __classcell__)r s@r!rr sO/`J#!%'#' $$% &%)#(&*"#!#(#))r#rN)r* transformers.configuration_utilsrmodelscope.utilsrlogging get_loggerrr r#r!r2s+#=.    \$\r#