nemo_automodel.components.models.kimi_k3
nemo_automodel.components.models.kimi_k3
Subpackages
Submodules
nemo_automodel.components.models.kimi_k3.attn_res_tritonnemo_automodel.components.models.kimi_k3.confignemo_automodel.components.models.kimi_k3.cpnemo_automodel.components.models.kimi_k3.encodingnemo_automodel.components.models.kimi_k3.modelnemo_automodel.components.models.kimi_k3.multimodalnemo_automodel.components.models.kimi_k3.situnemo_automodel.components.models.kimi_k3.situ_tritonnemo_automodel.components.models.kimi_k3.state_dict_adapternemo_automodel.components.models.kimi_k3.tokenizationnemo_automodel.components.models.kimi_k3.vision
Package Contents
Classes
API
Bases: PretrainedConfig
Top-level Kimi K3 vision-language checkpoint configuration.
Bases: PretrainedConfig
Configuration for the Kimi K3 hybrid KDA/MLA text backbone.
Defaults reproduce the released moonshotai/Kimi-K3 checkpoint (config.json text_config;
tech report Table 1): 93 layers (69 KDA + 24 gated MLA), 96 attention heads, dense FFN 33792,
896 latent-MoE experts (16 active, 2 shared), so from_config builds the same shape that
from_pretrained loads.
Whether any decoder layer uses Kimi Delta Attention.
Whether full-attention layers use Kimi multi-latent attention.
Whether the text checkpoint has routed experts.
Return whether zero-based layer_idx is a KDA layer.
Bases: PretrainedConfig
Configuration for the Kimi K3 MoonViT3d vision tower and projector.