Repository: ggerganov/llama.cpp
File: src/llama-arch.cpp (C++)

Code before:
    { LLM_KV_GENERAL_SOURCE_URL,           "general.source.url"                    },
    { LLM_KV_GENERAL_SOURCE_HF_REPO,       "general.source.huggingface.repository" },

    { LLM_KV_VOCAB_SIZE,                        "%s.vocab_size"                        },
    { LLM_KV_CONTEXT_LENGTH,                    "%s.context_length"                    },
    { LLM_KV_EMBEDDING_LENGTH,                  "%s.embedding_length"                  },
    { LLM_KV_FEATURES_LENGTH,                   "%s.features_length"                   },
    { LLM_KV_BLOCK_COUNT,                       "%s.block_count"                       },
    { LLM_KV_LEADING_DENSE_BLOCK_COUNT,         "%s.leading_dense_block_count"         },
    { LLM_KV_FEED_FORWARD_LENGTH,               "%s.feed_forward_length"               },
    { LLM_KV_EXPERT_FEED_FORWARD_LENGTH,        "%s.expert_feed_forward_length"        },
    { LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH, "%s.expert_shared_feed_forward_length" },
    { LLM_KV_USE_PARALLEL_RESIDUAL,             "%s.use_parallel_residual"             },
    { LLM_KV_TENSOR_DATA_LAYOUT,                "%s.tensor_data_layout"                },
    { LLM_KV_EXPERT_COUNT,                      "%s.expert_count"                      },
    { LLM_KV_EXPERT_USED_COUNT,                 "%s.expert_used_count"                 },
    { LLM_KV_EXPERT_SHARED_COUNT,               "%s.expert_shared_count"               },
    { LLM_KV_EXPERT_WEIGHTS_SCALE,              "%s.expert_weights_scale"              },
    { LLM_KV_EXPERT_WEIGHTS_NORM,               "%s.expert_weights_norm"               },
    { LLM_KV_EXPERT_GATING_FUNC,                "%s.expert_gating_func"                },
    { LLM_KV_MOE_EVERY_N_LAYERS,                "%s.moe_every_n_layers"                },
    { LLM_KV_NEXTN_PREDICT_LAYERS,              "%s.nextn_predict_layers"              },
    { LLM_KV_POOLING_TYPE,                      "%s.pooling_type"                      },
    { LLM_KV_LOGIT_SCALE,                       "%s.logit_scale"                       },
    { LLM_KV_DECODER_START_TOKEN_ID,            "%s.decoder_start_token_id"            },
    { LLM_KV_NUM_DECODER_LAYERS,                "%s.num_decoder_layers"                },
    { LLM_KV_ATTN_LOGIT_SOFTCAPPING,            "%s.attn_logit_softcapping"            },
    { LLM_KV_FINAL_LOGIT_SOFTCAPPING,           "%s.final_logit_softcapping"           },
    { LLM_KV_SWIN_NORM,                         "%s.swin_norm"                         },
    { LLM_KV_RESCALE_EVERY_N_LAYERS,            "%s.rescale_every_n_layers"            },
    { LLM_KV_TIME_MIX_EXTRA_DIM,                "%s.time_mix_extra_dim"                },
    { LLM_KV_TIME_DECAY_EXTRA_DIM,              "%s.time_decay_extra_dim"              },
    { LLM_KV_RESIDUAL_SCALE,                    "%s.residual_scale"                    },
    { LLM_KV_EMBEDDING_SCALE,                   "%s.embedding_scale"                   },
    { LLM_KV_TOKEN_SHIFT_COUNT,                 "%s.token_shift_count"                 },
    { LLM_KV_INTERLEAVE_MOE_LAYER_STEP,         "%s.interleave_moe_layer_step"         },

    { LLM_KV_ATTENTION_HEAD_COUNT,                   "%s.attention.head_count"                   },
    { LLM_KV_ATTENTION_HEAD_COUNT_KV,                "%s.attention.head_count_kv"                },
    { LLM_KV_ATTENTION_MAX_ALIBI_BIAS,               "%s.attention.max_alibi_bias"               },
    { LLM_KV_ATTENTION_CLAMP_KQV,                    "%s.attention.clamp_kqv"                    },
    { LLM_KV_ATTENTION_KEY_LENGTH,                   "%s.attention.key_length"                   },
    { LLM_KV_ATTENTION_VALUE_LENGTH,                 "%s.attention.value_length"                 },
    { LLM_KV_ATTENTION_LAYERNORM_EPS,                "%s.attention.layer_norm_epsilon"           },
    { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,            "%s.attention.layer_norm_rms_epsilon"       },
    { LLM_KV_ATTENTION_GROUPNORM_EPS,                "%s.attention.group_norm_epsilon"           },
    { LLM_KV_ATTENTION_GROUPNORM_GROUPS,             "%s.attention.group_norm_groups"            },
    { LLM_KV_ATTENTION_CAUSAL,                       "%s.attention.causal"                       },
    { LLM_KV_ATTENTION_Q_LORA_RANK,                  "%s.attention.q_lora_rank"                  },
    { LLM_KV_ATTENTION_KV_LORA_RANK,                 "%s.attention.kv_lora_rank"                 },
    { LLM_KV_ATTENTION_DECAY_LORA_RANK,              "%s.attention.decay_lora_rank"              },

Review comment (suggestion):
```suggestion
    { LLM_KV_DECODER_BLOCK_COUNT,               "%s.decoder_block_count"               },
```

Code after:
    { LLM_KV_GENERAL_SOURCE_URL,           "general.source.url"                    },
    { LLM_KV_GENERAL_SOURCE_HF_REPO,       "general.source.huggingface.repository" },

    { LLM_KV_VOCAB_SIZE,                        "%s.vocab_size"                        },
    { LLM_KV_CONTEXT_LENGTH,                    "%s.context_length"                    },
    { LLM_KV_EMBEDDING_LENGTH,                  "%s.embedding_length"                  },
    { LLM_KV_FEATURES_LENGTH,                   "%s.features_length"                   },
    { LLM_KV_BLOCK_COUNT,                       "%s.block_count"                       },
    { LLM_KV_LEADING_DENSE_BLOCK_COUNT,         "%s.leading_dense_block_count"         },
    { LLM_KV_FEED_FORWARD_LENGTH,               "%s.feed_forward_length"               },
    { LLM_KV_EXPERT_FEED_FORWARD_LENGTH,        "%s.expert_feed_forward_length"        },
    { LLM_KV_EXPERT_SHARED_FEED_FORWARD_LENGTH, "%s.expert_shared_feed_forward_length" },
    { LLM_KV_USE_PARALLEL_RESIDUAL,             "%s.use_parallel_residual"             },
    { LLM_KV_TENSOR_DATA_LAYOUT,                "%s.tensor_data_layout"                },
    { LLM_KV_EXPERT_COUNT,                      "%s.expert_count"                      },
    { LLM_KV_EXPERT_USED_COUNT,                 "%s.expert_used_count"                 },
    { LLM_KV_EXPERT_SHARED_COUNT,               "%s.expert_shared_count"               },
    { LLM_KV_EXPERT_WEIGHTS_SCALE,              "%s.expert_weights_scale"              },
    { LLM_KV_EXPERT_WEIGHTS_NORM,               "%s.expert_weights_norm"               },
    { LLM_KV_EXPERT_GATING_FUNC,                "%s.expert_gating_func"                },
    { LLM_KV_MOE_EVERY_N_LAYERS,                "%s.moe_every_n_layers"                },
    { LLM_KV_NEXTN_PREDICT_LAYERS,              "%s.nextn_predict_layers"              },
    { LLM_KV_POOLING_TYPE,                      "%s.pooling_type"                      },
    { LLM_KV_LOGIT_SCALE,                       "%s.logit_scale"                       },
    { LLM_KV_DECODER_START_TOKEN_ID,            "%s.decoder_start_token_id"            },
    { LLM_KV_DECODER_BLOCK_COUNT,               "%s.decoder_block_count"               },
    { LLM_KV_ATTN_LOGIT_SOFTCAPPING,            "%s.attn_logit_softcapping"            },
    { LLM_KV_FINAL_LOGIT_SOFTCAPPING,           "%s.final_logit_softcapping"           },
    { LLM_KV_SWIN_NORM,                         "%s.swin_norm"                         },
    { LLM_KV_RESCALE_EVERY_N_LAYERS,            "%s.rescale_every_n_layers"            },
    { LLM_KV_TIME_MIX_EXTRA_DIM,                "%s.time_mix_extra_dim"                },
    { LLM_KV_TIME_DECAY_EXTRA_DIM,              "%s.time_decay_extra_dim"              },
    { LLM_KV_RESIDUAL_SCALE,                    "%s.residual_scale"                    },
    { LLM_KV_EMBEDDING_SCALE,                   "%s.embedding_scale"                   },
    { LLM_KV_TOKEN_SHIFT_COUNT,                 "%s.token_shift_count"                 },
    { LLM_KV_INTERLEAVE_MOE_LAYER_STEP,         "%s.interleave_moe_layer_step"         },

    { LLM_KV_ATTENTION_HEAD_COUNT,                   "%s.attention.head_count"                   },
    { LLM_KV_ATTENTION_HEAD_COUNT_KV,                "%s.attention.head_count_kv"                },
    { LLM_KV_ATTENTION_MAX_ALIBI_BIAS,               "%s.attention.max_alibi_bias"               },
    { LLM_KV_ATTENTION_CLAMP_KQV,                    "%s.attention.clamp_kqv"                    },
    { LLM_KV_ATTENTION_KEY_LENGTH,                   "%s.attention.key_length"                   },
    { LLM_KV_ATTENTION_VALUE_LENGTH,                 "%s.attention.value_length"                 },
    { LLM_KV_ATTENTION_LAYERNORM_EPS,                "%s.attention.layer_norm_epsilon"           },
    { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,            "%s.attention.layer_norm_rms_epsilon"       },
    { LLM_KV_ATTENTION_GROUPNORM_EPS,                "%s.attention.group_norm_epsilon"           },
    { LLM_KV_ATTENTION_GROUPNORM_GROUPS,             "%s.attention.group_norm_groups"            },
    { LLM_KV_ATTENTION_CAUSAL,                       "%s.attention.causal"                       },
    { LLM_KV_ATTENTION_Q_LORA_RANK,                  "%s.attention.q_lora_rank"                  },
    { LLM_KV_ATTENTION_KV_LORA_RANK,                 "%s.attention.kv_lora_rank"                 },
    { LLM_KV_ATTENTION_DECAY_LORA_RANK,              "%s.attention.decay_lora_rank"              },