+ jr t^RIHt^RIHt^RIHt^RIHt]!RR7]!RR]444tR.t R #) )strict)PreTrainedConfig)RopeParameters)auto_docstringzLiquidAI/LFM2-1.2B) checkpointcaa]tRt^toRtRtR.tRtRtRt Rt ^ t ^ t ^t RtR tR tR t^t^t^tR tR tR t^tRtRtR tR tR tV3RltV3RltRt Vt!V;t"#) Lfm2Configa conv_bias (`bool`, *optional*, defaults to `False`): Whether to use bias in the conv layers. conv_L_cache (`int`, *optional*, defaults to 3): L_cache dim in the conv layers. block_multiple_of (`int`, *optional*, defaults to 256): Multiple for the `intermediate_size`. block_ffn_dim_multiplier (`float`, *optional*, defaults to 1.0): Multiplier for the `intermediate_size`. block_auto_adjust_ff_dim (`bool`, *optional*, defaults to `True`): Whether to adjust the dim of the `intermediate_size`. full_attn_idxs (`Optional`, *optional*): Index of the layers which use attention. ```python >>> from transformers import Lfm2Model, Lfm2Config >>> # Initializing a LFM2 model >>> configuration = Lfm2Config() >>> # Initializing a model from the LFM2-1.2B style configuration >>> model = Lfm2Model(configuration) >>> # Accessing the model configuration >>> configuration = model.config ``` lfm2past_key_valuesg.Aii i0ig{Gz?gh㈵>TNFg?c <VPfzVPe VPM\\VP44Vn\VP4Uu.uFq"VP9dRMRNK upVnVP RVP 4VnVP RVP4Vn\SV`$!R/VBR#uupi)Nfull_attentionconv tie_embedding block_ff_dim) layer_typesfull_attn_idxslistrangenum_hidden_layerspoptie_word_embeddingsintermediate_sizesuper __post_init__)selfkwargsi __class__s&, l/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/lfm2/configuration_lfm2.pyrLfm2Config.__post_init__Qs    #'+':':'F##DQVW[WmWmQnLo  SXX\XnXnRo RoQ)<)<$< &HRo D $*::ot?W?W#X !'NDrQsJ /31#/0C(!C(1C(L .r?