Zj dSrSSKJr SSKJr SSKJr \"SS9\"SS \555rS /rg ) zCPMAnt model configuration)strict)PreTrainedConfig)auto_docstringzopenbmb/cpm-ant-10b) checkpointc\rSrSr%SrSrSr\\S'Sr \\S'Sr \\S 'S r \\S 'S r \\S 'Sr \\S'Sr\\-\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'Sr\\S'S rg!)" CpmAntConfiga 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). 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. 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 ```cpmantix vocab_sizei hidden_size num_attention_headsdim_headi(dim_ff0num_hidden_layersg dropout_piposition_bias_num_bucketsiposition_bias_max_distancegư>epsg?init_std prompt_types prompt_length segment_typesT use_cachetie_word_embeddingsN)__name__ __module__ __qualname____firstlineno____doc__ model_typer int__annotations__r rrrrrfloatrrrrrrrrboolr__static_attributes__rڀ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/cpmant/configuration_cpmant.pyr r s 8JJK!!HcFCs Ius{ %(s(&**CHeL#M3M3It $$r+r N) r$huggingface_hub.dataclassesrconfiguration_utilsrutilsrr __all__rr+r,r1sH!.3#01.%#.%2.%b  r+