llama.cpp LLM_ARCH_DEEPSEEK and LLM_ARCH_DEEPSEEK2
- 1. `LLM_ARCH_DEEPSEEK` and `LLM_ARCH_DEEPSEEK2`
- 2. `LLM_ARCH_DEEPSEEK` and `LLM_ARCH_DEEPSEEK2`
- 3. `struct ggml_cgraph * build_deepseek()` and `struct ggml_cgraph * build_deepseek2()`
- References
不宜吹捧中国大语言模型的同时，又去贬低美国大语言模型。
水是人体的主要化学成分，约占体重的 50% 至 70%。大语言模型的含水量也不会太少。
llama.cpp
https://github.com/ggerganov/llama.cpp
1. LLM_ARCH_DEEPSEEK and LLM_ARCH_DEEPSEEK2
/home/yongqiang/llm_work/llama_cpp_25_01_05/llama.cpp/src/llama-arch.h
/home/yongqiang/llm_work/llama_cpp_25_01_05/llama.cpp/src/llama-arch.cpp
LLM_ARCH_DEEPSEEKandLLM_ARCH_DEEPSEEK2
//
// gguf constants (sync with gguf.py)
//enum llm_arch {LLM_ARCH_LLAMA,LLM_ARCH_DECI,LLM_ARCH_FALCON,LLM_ARCH_BAICHUAN,LLM_ARCH_GROK,LLM_ARCH_GPT2,LLM_ARCH_GPTJ,LLM_ARCH_GPTNEOX,LLM_ARCH_MPT,LLM_ARCH_STARCODER,LLM_ARCH_REFACT,LLM_ARCH_BERT,LLM_ARCH_NOMIC_BERT,LLM_ARCH_JINA_BERT_V2,LLM_ARCH_BLOOM,LLM_ARCH_STABLELM,LLM_ARCH_QWEN,LLM_ARCH_QWEN2,LLM_ARCH_QWEN2MOE,LLM_ARCH_QWEN2VL,LLM_ARCH_PHI2,LLM_ARCH_PHI3,LLM_ARCH_PHIMOE,LLM_ARCH_PLAMO,LLM_ARCH_CODESHELL,LLM_ARCH_ORION,LLM_ARCH_INTERNLM2,LLM_ARCH_MINICPM,LLM_ARCH_MINICPM3,LLM_ARCH_GEMMA,LLM_ARCH_GEMMA2,LLM_ARCH_STARCODER2,LLM_ARCH_MAMBA,LLM_ARCH_XVERSE,LLM_ARCH_COMMAND_R,LLM_ARCH_COHERE2,LLM_ARCH_DBRX,LLM_ARCH_OLMO,LLM_ARCH_OLMO2,LLM_ARCH_OLMOE,LLM_ARCH_OPENELM,LLM_ARCH_ARCTIC,LLM_ARCH_DEEPSEEK,LLM_ARCH_DEEPSEEK2,LLM_ARCH_CHATGLM,LLM_ARCH_BITNET,LLM_ARCH_T5,LLM_ARCH_T5ENCODER,LLM_ARCH_JAIS,LLM_ARCH_NEMOTRON,LLM_ARCH_EXAONE,LLM_ARCH_RWKV6,LLM_ARCH_RWKV6QWEN2,LLM_ARCH_GRANITE,LLM_ARCH_GRANITE_MOE,LLM_ARCH_CHAMELEON,LLM_ARCH_WAVTOKENIZER_DEC,LLM_ARCH_UNKNOWN,
};
{ LLM_ARCH_DEEPSEEK, "deepseek" }and{ LLM_ARCH_DEEPSEEK2, "deepseek2" }
static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {{ LLM_ARCH_LLAMA, "llama" },{ LLM_ARCH_DECI, "deci" },{ LLM_ARCH_FALCON, "falcon" },{ LLM_ARCH_GROK, "grok" },{ LLM_ARCH_GPT2, "gpt2" },{ LLM_ARCH_GPTJ, "gptj" },{ LLM_ARCH_GPTNEOX, "gptneox" },{ LLM_ARCH_MPT, "mpt" },{ LLM_ARCH_BAICHUAN, "baichuan" },{ LLM_ARCH_STARCODER, "starcoder" },{ LLM_ARCH_REFACT, "refact" },{ LLM_ARCH_BERT, "bert" },{ LLM_ARCH_NOMIC_BERT, "nomic-bert" },{ LLM_ARCH_JINA_BERT_V2, "jina-bert-v2" },{ LLM_ARCH_BLOOM, "bloom" },{ LLM_ARCH_STABLELM, "stablelm" },{ LLM_ARCH_QWEN, "qwen" },{ LLM_ARCH_QWEN2, "qwen2" },{ LLM_ARCH_QWEN2MOE, "qwen2moe" },{ LLM_ARCH_QWEN2VL, "qwen2vl" },{ LLM_ARCH_PHI2, "phi2" },{ LLM_ARCH_PHI3, "phi3" },{ LLM_ARCH_PHIMOE, "phimoe" },{ LLM_ARCH_PLAMO, "plamo" },{ LLM_ARCH_CODESHELL, "codeshell" },{ LLM_ARCH_ORION, "orion" },{ LLM_ARCH_INTERNLM2, "internlm2" },{ LLM_ARCH_MINICPM, "minicpm" },{ LLM_ARCH_MINICPM3, "minicpm3" },{ LLM_ARCH_GEMMA, "gemma" },{ LLM_ARCH_GEMMA2, "gemma2" },{ LLM_ARCH_STARCODER2, "starcoder2" },{ LLM_ARCH_MAMBA, "mamba" },{ LLM_ARCH_XVERSE, "xverse" },{ LLM_ARCH_COMMAND_R, "command-r" },{ LLM_ARCH_COHERE2, "cohere2" },{ LLM_ARCH_DBRX, "dbrx" },{ LLM_ARCH_OLMO, "olmo" },{ LLM_ARCH_OLMO2, "olmo2" },{ LLM_ARCH_OLMOE, "olmoe" },{ LLM_ARCH_OPENELM, "openelm" },{ LLM_ARCH_ARCTIC, "arctic" },{ LLM_ARCH_DEEPSEEK, "deepseek" },{ LLM_ARCH_DEEPSEEK2, "deepseek2" },{ LLM_ARCH_CHATGLM, "chatglm" },{ LLM_ARCH_BITNET, "bitnet" },{ LLM_ARCH_T5, "t5" },{ LLM_ARCH_T5ENCODER, "t5encoder" },{ LLM_ARCH_JAIS, "jais" },{ LLM_ARCH_NEMOTRON, "nemotron" },{ LLM_ARCH_EXAONE, "exaone" },{ LLM_ARCH_RWKV6, "rwkv6" },{ LLM_ARCH_RWKV6QWEN2, "rwkv6qwen2" },{ LLM_ARCH_GRANITE, "granite" },{ LLM_ARCH_GRANITE_MOE, "granitemoe" },{ LLM_ARCH_CHAMELEON, "chameleon" },{ LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" },{ LLM_ARCH_UNKNOWN, "(unknown)" },
};
2. LLM_ARCH_DEEPSEEK and LLM_ARCH_DEEPSEEK2
/home/yongqiang/llm_work/llama_cpp_25_01_05/llama.cpp/src/llama-arch.cpp
LLM_ARCH_DEEPSEEKandLLM_ARCH_DEEPSEEK2
static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_NAMES = {{LLM_ARCH_LLAMA,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_GATE_EXP, "blk.%d.ffn_gate.%d" },{ LLM_TENSOR_FFN_DOWN_EXP, "blk.%d.ffn_down.%d" },{ LLM_TENSOR_FFN_UP_EXP, "blk.%d.ffn_up.%d" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_DECI,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_GATE_EXP, "blk.%d.ffn_gate.%d" },{ LLM_TENSOR_FFN_DOWN_EXP, "blk.%d.ffn_down.%d" },{ LLM_TENSOR_FFN_UP_EXP, "blk.%d.ffn_up.%d" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_BAICHUAN,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_FALCON,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_NORM_2, "blk.%d.attn_norm_2" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_GROK,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE_EXP, "blk.%d.ffn_gate.%d" },{ LLM_TENSOR_FFN_DOWN_EXP, "blk.%d.ffn_down.%d" },{ LLM_TENSOR_FFN_UP_EXP, "blk.%d.ffn_up.%d" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },{ LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" },{ LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" },},},{LLM_ARCH_GPT2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_POS_EMBD, "position_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_GPTJ,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },},},{LLM_ARCH_GPTNEOX,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_MPT,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output"},{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_ACT, "blk.%d.ffn.act" },{ LLM_TENSOR_POS_EMBD, "position_embd" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm"},{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm"},},},{LLM_ARCH_STARCODER,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_POS_EMBD, "position_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_REFACT,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_BERT,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_TOKEN_TYPES, "token_types" },{ LLM_TENSOR_POS_EMBD, "position_embd" },{ LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_CLS, "cls" },{ LLM_TENSOR_CLS_OUT, "cls.output" },},},{LLM_ARCH_NOMIC_BERT,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_TOKEN_TYPES, "token_types" },{ LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_JINA_BERT_V2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_TOKEN_TYPES, "token_types" },{ LLM_TENSOR_ATTN_NORM_2, "blk.%d.attn_norm_2" },{ LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_LAYER_OUT_NORM, "blk.%d.layer_output_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_CLS, "cls" },},},{LLM_ARCH_BLOOM,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_STABLELM,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },},},{LLM_ARCH_QWEN,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_QWEN2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_QWEN2VL,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_QWEN2MOE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },{ LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" },{ LLM_TENSOR_FFN_GATE_SHEXP, "blk.%d.ffn_gate_shexp" },{ LLM_TENSOR_FFN_DOWN_SHEXP, "blk.%d.ffn_down_shexp" },{ LLM_TENSOR_FFN_UP_SHEXP, "blk.%d.ffn_up_shexp" },},},{LLM_ARCH_PHI2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_PHI3,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FACTORS_LONG, "rope_factors_long" },{ LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_PHIMOE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FACTORS_LONG, "rope_factors_long" },{ LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_PLAMO,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_CODESHELL,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_ORION,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_INTERNLM2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_MINICPM,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ROPE_FACTORS_LONG, "rope_factors_long" },{ LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_GATE_EXP, "blk.%d.ffn_gate.%d" },{ LLM_TENSOR_FFN_DOWN_EXP, "blk.%d.ffn_down.%d" },{ LLM_TENSOR_FFN_UP_EXP, "blk.%d.ffn_up.%d" },},},{LLM_ARCH_MINICPM3,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FACTORS_LONG, "rope_factors_long" },{ LLM_TENSOR_ROPE_FACTORS_SHORT, "rope_factors_short" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q_A_NORM, "blk.%d.attn_q_a_norm" },{ LLM_TENSOR_ATTN_KV_A_NORM, "blk.%d.attn_kv_a_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_Q_A, "blk.%d.attn_q_a" },{ LLM_TENSOR_ATTN_Q_B, "blk.%d.attn_q_b" },{ LLM_TENSOR_ATTN_KV_A_MQA, "blk.%d.attn_kv_a_mqa" },{ LLM_TENSOR_ATTN_KV_B, "blk.%d.attn_kv_b" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_GEMMA,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_GEMMA2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" },},},{LLM_ARCH_STARCODER2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_MAMBA,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_SSM_IN, "blk.%d.ssm_in" },{ LLM_TENSOR_SSM_CONV1D, "blk.%d.ssm_conv1d" },{ LLM_TENSOR_SSM_X, "blk.%d.ssm_x" },{ LLM_TENSOR_SSM_DT, "blk.%d.ssm_dt" },{ LLM_TENSOR_SSM_A, "blk.%d.ssm_a" },{ LLM_TENSOR_SSM_D, "blk.%d.ssm_d" },{ LLM_TENSOR_SSM_OUT, "blk.%d.ssm_out" },},},{LLM_ARCH_XVERSE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_COMMAND_R,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },},},{LLM_ARCH_COHERE2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_DBRX,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_OUT_NORM, "blk.%d.attn_output_norm" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_OLMO,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_OLMO2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },{ LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_OLMOE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_OPENELM,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_ARCTIC,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_NORM_EXPS, "blk.%d.ffn_norm_exps" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_DEEPSEEK,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },{ LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" },{ LLM_TENSOR_FFN_GATE_SHEXP, "blk.%d.ffn_gate_shexp" },{ LLM_TENSOR_FFN_DOWN_SHEXP, "blk.%d.ffn_down_shexp" },{ LLM_TENSOR_FFN_UP_SHEXP, "blk.%d.ffn_up_shexp" },},},{LLM_ARCH_DEEPSEEK2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q_A_NORM, "blk.%d.attn_q_a_norm" },{ LLM_TENSOR_ATTN_KV_A_NORM, "blk.%d.attn_kv_a_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_Q_A, "blk.%d.attn_q_a" },{ LLM_TENSOR_ATTN_Q_B, "blk.%d.attn_q_b" },{ LLM_TENSOR_ATTN_KV_A_MQA, "blk.%d.attn_kv_a_mqa" },{ LLM_TENSOR_ATTN_KV_B, "blk.%d.attn_kv_b" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },{ LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" },{ LLM_TENSOR_FFN_GATE_SHEXP, "blk.%d.ffn_gate_shexp" },{ LLM_TENSOR_FFN_DOWN_SHEXP, "blk.%d.ffn_down_shexp" },{ LLM_TENSOR_FFN_UP_SHEXP, "blk.%d.ffn_up_shexp" },{ LLM_TENSOR_FFN_EXP_PROBS_B, "blk.%d.exp_probs_b" },},},{LLM_ARCH_CHATGLM,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_BITNET,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_SUB_NORM, "blk.%d.attn_sub_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_SUB_NORM, "blk.%d.ffn_sub_norm" },},},{LLM_ARCH_T5,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_DEC_OUTPUT_NORM, "dec.output_norm" },{ LLM_TENSOR_DEC_ATTN_NORM, "dec.blk.%d.attn_norm" },{ LLM_TENSOR_DEC_ATTN_Q, "dec.blk.%d.attn_q" },{ LLM_TENSOR_DEC_ATTN_K, "dec.blk.%d.attn_k" },{ LLM_TENSOR_DEC_ATTN_V, "dec.blk.%d.attn_v" },{ LLM_TENSOR_DEC_ATTN_OUT, "dec.blk.%d.attn_o" },{ LLM_TENSOR_DEC_ATTN_REL_B, "dec.blk.%d.attn_rel_b" },{ LLM_TENSOR_DEC_CROSS_ATTN_NORM, "dec.blk.%d.cross_attn_norm" },{ LLM_TENSOR_DEC_CROSS_ATTN_Q, "dec.blk.%d.cross_attn_q" },{ LLM_TENSOR_DEC_CROSS_ATTN_K, "dec.blk.%d.cross_attn_k" },{ LLM_TENSOR_DEC_CROSS_ATTN_V, "dec.blk.%d.cross_attn_v" },{ LLM_TENSOR_DEC_CROSS_ATTN_OUT, "dec.blk.%d.cross_attn_o" },{ LLM_TENSOR_DEC_CROSS_ATTN_REL_B, "dec.blk.%d.cross_attn_rel_b" },{ LLM_TENSOR_DEC_FFN_NORM, "dec.blk.%d.ffn_norm" },{ LLM_TENSOR_DEC_FFN_GATE, "dec.blk.%d.ffn_gate" },{ LLM_TENSOR_DEC_FFN_DOWN, "dec.blk.%d.ffn_down" },{ LLM_TENSOR_DEC_FFN_UP, "dec.blk.%d.ffn_up" },{ LLM_TENSOR_ENC_OUTPUT_NORM, "enc.output_norm" },{ LLM_TENSOR_ENC_ATTN_NORM, "enc.blk.%d.attn_norm" },{ LLM_TENSOR_ENC_ATTN_Q, "enc.blk.%d.attn_q" },{ LLM_TENSOR_ENC_ATTN_K, "enc.blk.%d.attn_k" },{ LLM_TENSOR_ENC_ATTN_V, "enc.blk.%d.attn_v" },{ LLM_TENSOR_ENC_ATTN_OUT, "enc.blk.%d.attn_o" },{ LLM_TENSOR_ENC_ATTN_REL_B, "enc.blk.%d.attn_rel_b" },{ LLM_TENSOR_ENC_FFN_NORM, "enc.blk.%d.ffn_norm" },{ LLM_TENSOR_ENC_FFN_GATE, "enc.blk.%d.ffn_gate" },{ LLM_TENSOR_ENC_FFN_DOWN, "enc.blk.%d.ffn_down" },{ LLM_TENSOR_ENC_FFN_UP, "enc.blk.%d.ffn_up" },},},{LLM_ARCH_T5ENCODER,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ENC_OUTPUT_NORM, "enc.output_norm" },{ LLM_TENSOR_ENC_ATTN_NORM, "enc.blk.%d.attn_norm" },{ LLM_TENSOR_ENC_ATTN_Q, "enc.blk.%d.attn_q" },{ LLM_TENSOR_ENC_ATTN_K, "enc.blk.%d.attn_k" },{ LLM_TENSOR_ENC_ATTN_V, "enc.blk.%d.attn_v" },{ LLM_TENSOR_ENC_ATTN_OUT, "enc.blk.%d.attn_o" },{ LLM_TENSOR_ENC_ATTN_REL_B, "enc.blk.%d.attn_rel_b" },{ LLM_TENSOR_ENC_FFN_NORM, "enc.blk.%d.ffn_norm" },{ LLM_TENSOR_ENC_FFN_GATE, "enc.blk.%d.ffn_gate" },{ LLM_TENSOR_ENC_FFN_DOWN, "enc.blk.%d.ffn_down" },{ LLM_TENSOR_ENC_FFN_UP, "enc.blk.%d.ffn_up" },},},{LLM_ARCH_JAIS,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_QKV, "blk.%d.attn_qkv" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },},},{LLM_ARCH_NEMOTRON,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_EXAONE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ROPE_FREQS, "rope_freqs" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_ATTN_ROT_EMBD, "blk.%d.attn_rot_embd" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_RWKV6,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_NORM_2, "blk.%d.attn_norm_2" },{ LLM_TENSOR_TIME_MIX_W1, "blk.%d.time_mix_w1" },{ LLM_TENSOR_TIME_MIX_W2, "blk.%d.time_mix_w2" },{ LLM_TENSOR_TIME_MIX_LERP_X, "blk.%d.time_mix_lerp_x" },{ LLM_TENSOR_TIME_MIX_LERP_W, "blk.%d.time_mix_lerp_w" },{ LLM_TENSOR_TIME_MIX_LERP_K, "blk.%d.time_mix_lerp_k" },{ LLM_TENSOR_TIME_MIX_LERP_V, "blk.%d.time_mix_lerp_v" },{ LLM_TENSOR_TIME_MIX_LERP_R, "blk.%d.time_mix_lerp_r" },{ LLM_TENSOR_TIME_MIX_LERP_G, "blk.%d.time_mix_lerp_g" },{ LLM_TENSOR_TIME_MIX_LERP_FUSED, "blk.%d.time_mix_lerp_fused" },{ LLM_TENSOR_TIME_MIX_FIRST, "blk.%d.time_mix_first" },{ LLM_TENSOR_TIME_MIX_DECAY, "blk.%d.time_mix_decay" },{ LLM_TENSOR_TIME_MIX_DECAY_W1, "blk.%d.time_mix_decay_w1" },{ LLM_TENSOR_TIME_MIX_DECAY_W2, "blk.%d.time_mix_decay_w2" },{ LLM_TENSOR_TIME_MIX_KEY, "blk.%d.time_mix_key" },{ LLM_TENSOR_TIME_MIX_VALUE, "blk.%d.time_mix_value" },{ LLM_TENSOR_TIME_MIX_RECEPTANCE, "blk.%d.time_mix_receptance" },{ LLM_TENSOR_TIME_MIX_GATE, "blk.%d.time_mix_gate" },{ LLM_TENSOR_TIME_MIX_LN, "blk.%d.time_mix_ln" },{ LLM_TENSOR_TIME_MIX_OUTPUT, "blk.%d.time_mix_output" },{ LLM_TENSOR_CHANNEL_MIX_LERP_K, "blk.%d.channel_mix_lerp_k" },{ LLM_TENSOR_CHANNEL_MIX_LERP_R, "blk.%d.channel_mix_lerp_r" },{ LLM_TENSOR_CHANNEL_MIX_KEY, "blk.%d.channel_mix_key" },{ LLM_TENSOR_CHANNEL_MIX_VALUE, "blk.%d.channel_mix_value" },{ LLM_TENSOR_CHANNEL_MIX_RECEPTANCE, "blk.%d.channel_mix_receptance" },},},{LLM_ARCH_RWKV6QWEN2,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_TIME_MIX_W1, "blk.%d.time_mix_w1" },{ LLM_TENSOR_TIME_MIX_W2, "blk.%d.time_mix_w2" },{ LLM_TENSOR_TIME_MIX_LERP_X, "blk.%d.time_mix_lerp_x" },{ LLM_TENSOR_TIME_MIX_LERP_FUSED, "blk.%d.time_mix_lerp_fused" },{ LLM_TENSOR_TIME_MIX_FIRST, "blk.%d.time_mix_first" },{ LLM_TENSOR_TIME_MIX_DECAY, "blk.%d.time_mix_decay" },{ LLM_TENSOR_TIME_MIX_DECAY_W1, "blk.%d.time_mix_decay_w1" },{ LLM_TENSOR_TIME_MIX_DECAY_W2, "blk.%d.time_mix_decay_w2" },{ LLM_TENSOR_TIME_MIX_KEY, "blk.%d.time_mix_key" },{ LLM_TENSOR_TIME_MIX_VALUE, "blk.%d.time_mix_value" },{ LLM_TENSOR_TIME_MIX_RECEPTANCE, "blk.%d.time_mix_receptance" },{ LLM_TENSOR_TIME_MIX_GATE, "blk.%d.time_mix_gate" },{ LLM_TENSOR_TIME_MIX_OUTPUT, "blk.%d.time_mix_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_GRANITE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },},},{LLM_ARCH_GRANITE_MOE,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },},},{LLM_ARCH_CHAMELEON,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },{ LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },{ LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },{ LLM_TENSOR_ATTN_Q_NORM, "blk.%d.attn_q_norm" },{ LLM_TENSOR_ATTN_K_NORM, "blk.%d.attn_k_norm" },},},{LLM_ARCH_WAVTOKENIZER_DEC,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },{ LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },{ LLM_TENSOR_CONV1D, "conv1d" },{ LLM_TENSOR_CONVNEXT_DW, "convnext.%d.dw" },{ LLM_TENSOR_CONVNEXT_NORM, "convnext.%d.norm" },{ LLM_TENSOR_CONVNEXT_PW1, "convnext.%d.pw1" },{ LLM_TENSOR_CONVNEXT_PW2, "convnext.%d.pw2" },{ LLM_TENSOR_CONVNEXT_GAMMA, "convnext.%d.gamma" },{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },{ LLM_TENSOR_OUTPUT, "output" },{ LLM_TENSOR_POS_NET_CONV1, "posnet.%d.conv1" },{ LLM_TENSOR_POS_NET_CONV2, "posnet.%d.conv2" },{ LLM_TENSOR_POS_NET_NORM, "posnet.%d.norm" },{ LLM_TENSOR_POS_NET_NORM1, "posnet.%d.norm1" },{ LLM_TENSOR_POS_NET_NORM2, "posnet.%d.norm2" },{ LLM_TENSOR_POS_NET_ATTN_NORM, "posnet.%d.attn_norm" },{ LLM_TENSOR_POS_NET_ATTN_Q, "posnet.%d.attn_q" },{ LLM_TENSOR_POS_NET_ATTN_K, "posnet.%d.attn_k" },{ LLM_TENSOR_POS_NET_ATTN_V, "posnet.%d.attn_v" },{ LLM_TENSOR_POS_NET_ATTN_OUT, "posnet.%d.attn_output" },},},{LLM_ARCH_UNKNOWN,{{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },},},
};
3. struct ggml_cgraph * build_deepseek() and struct ggml_cgraph * build_deepseek2()
/home/yongqiang/llm_work/llama_cpp_25_01_05/llama.cpp/src/llama.cpp
struct ggml_cgraph * build_deepseek()
struct ggml_cgraph * build_deepseek() {struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, model.max_nodes(), false);// mutable variable, needed during the last layer of the computation to skip unused tokensint32_t n_tokens = this->n_tokens;const int64_t n_embd_head = hparams.n_embd_head_v;GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);GGML_ASSERT(n_embd_head == hparams.n_rot);struct ggml_tensor * cur;struct ggml_tensor * inpL;inpL = llm_build_inp_embd(ctx0, lctx, hparams, ubatch, model.tok_embd, cb);// inp_pos - contains the positionsstruct ggml_tensor * inp_pos = build_inp_pos();// KQ_mask (mask for 1 head, it will be broadcasted to all heads)struct ggml_tensor * KQ_mask = build_inp_KQ_mask();const float kq_scale = hparams.f_attention_scale == 0.0f ? 1.0f/sqrtf(float(n_embd_head)) : hparams.f_attention_scale;for (int il = 0; il < n_layer; ++il) {struct ggml_tensor * inpSA = inpL;// normcur = llm_build_norm(ctx0, inpL, hparams,model.layers[il].attn_norm, NULL,LLM_NORM_RMS, cb, il);cb(cur, "attn_norm", il);// self-attention{// rope freq factors for llama3; may return nullptr for llama2 and other modelsstruct ggml_tensor * rope_factors = build_rope_factors(il);// compute Q and K and RoPE themstruct ggml_tensor * Qcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wq, cur);cb(Qcur, "Qcur", il);if (model.layers[il].bq) {Qcur = ggml_add(ctx0, Qcur, model.layers[il].bq);cb(Qcur, "Qcur", il);}struct ggml_tensor * Kcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wk, cur);cb(Kcur, "Kcur", il);if (model.layers[il].bk) {Kcur = ggml_add(ctx0, Kcur, model.layers[il].bk);cb(Kcur, "Kcur", il);}struct ggml_tensor * Vcur = llm_build_lora_mm(lctx, ctx0, model.layers[il].wv, cur);cb(Vcur, "Vcur", il);if (model.layers[il].bv) {Vcur = ggml_add(ctx0, Vcur, model.layers[il].bv);cb(Vcur, "Vcur", il);}Qcur = ggml_rope_ext(ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos, rope_factors,n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,ext_factor, attn_factor, beta_fast, beta_slow);cb(Qcur, "Qcur", il);Kcur = ggml_rope_ext(ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens), inp_pos, rope_factors,n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,ext_factor, attn_factor, beta_fast, beta_slow);cb(Kcur, "Kcur", il);cur = llm_build_kv(ctx0, lctx, kv_self, gf,model.layers[il].wo, model.layers[il].bo,Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, kq_scale, cb, il);}if (il == n_layer - 1) {// skip computing output for unused tokensstruct ggml_tensor * inp_out_ids = build_inp_out_ids();n_tokens = n_outputs;cur = ggml_get_rows(ctx0, cur, inp_out_ids);inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);}struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);cb(ffn_inp, "ffn_inp", il);cur = llm_build_norm(ctx0, ffn_inp, hparams,model.layers[il].ffn_norm, NULL,LLM_NORM_RMS, cb, il);cb(cur, "ffn_norm", il);if ((uint32_t) il < hparams.n_layer_dense_lead) {cur = llm_build_ffn(ctx0, lctx, cur,model.layers[il].ffn_up, NULL, NULL,model.layers[il].ffn_gate, NULL, NULL,model.layers[il].ffn_down, NULL, NULL,NULL,LLM_FFN_SILU, LLM_FFN_PAR, cb, il);cb(cur, "ffn_out", il);} else {// MoE branchggml_tensor * moe_out =llm_build_moe_ffn(ctx0, lctx, cur,model.layers[il].ffn_gate_inp,model.layers[il].ffn_up_exps,model.layers[il].ffn_gate_exps,model.layers[il].ffn_down_exps,nullptr,n_expert, n_expert_used,LLM_FFN_SILU, false,false, hparams.expert_weights_scale,LLAMA_EXPERT_GATING_FUNC_TYPE_SOFTMAX,cb, il);cb(moe_out, "ffn_moe_out", il);// FFN shared expert{ggml_tensor * ffn_shexp = llm_build_ffn(ctx0, lctx, cur,model.layers[il].ffn_up_shexp, NULL, NULL,model.layers[il].ffn_gate_shexp, NULL, NULL,model.layers[il].ffn_down_shexp, NULL, NULL,NULL,LLM_FFN_SILU, LLM_FFN_PAR, cb, il);cb(ffn_shexp, "ffn_shexp", il);cur = ggml_add(ctx0, moe_out, ffn_shexp);cb(cur, "ffn_out", il);}}cur = ggml_add(ctx0, cur, ffn_inp);cur = lctx.cvec.apply_to(ctx0, cur, il);cb(cur, "l_out", il);// input for next layerinpL = cur;}cur = inpL;cur = llm_build_norm(ctx0, cur, hparams,model.output_norm, NULL,LLM_NORM_RMS, cb, -1);cb(cur, "result_norm", -1);// lm_headcur = llm_build_lora_mm(lctx, ctx0, model.output, cur);cb(cur, "result_output", -1);ggml_build_forward_expand(gf, cur);return gf;}
struct ggml_cgraph * build_deepseek2()
struct ggml_cgraph * build_deepseek2() {struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, model.max_nodes(), false);// mutable variable, needed during the last layer of the computation to skip unused tokensint32_t n_tokens = this->n_tokens;bool is_lite = (hparams.n_layer == 27);// We have to pre-scale kq_scale and attn_factor to make the YaRN RoPE work correctly.// See https://github.com/ggerganov/llama.cpp/discussions/7416 for detailed explanation.const float mscale = attn_factor * (1.0f + hparams.rope_yarn_log_mul * logf(1.0f / freq_scale));const float kq_scale = 1.0f*mscale*mscale/sqrtf(float(hparams.n_embd_head_k));const float attn_factor_scaled = 1.0f / (1.0f + 0.1f * logf(1.0f / freq_scale));const uint32_t n_embd_head_qk_rope = hparams.n_rot;const uint32_t n_embd_head_qk_nope = hparams.n_embd_head_k - hparams.n_rot;const uint32_t kv_lora_rank = hparams.n_lora_kv;struct ggml_tensor * cur;struct ggml_tensor * inpL;// {n_embd, n_tokens}inpL = llm_build_inp_embd(ctx0, lctx, hparams, ubatch, model.tok_embd, cb);// inp_pos - contains the positionsstruct ggml_tensor * inp_pos = build_inp_pos();// KQ_mask (mask for 1 head, it will be broadcasted to all heads)struct ggml_tensor * KQ_mask = build_inp_KQ_mask();for (int il = 0; il < n_layer; ++il) {struct ggml_tensor * inpSA = inpL;// normcur = llm_build_norm(ctx0, inpL, hparams,model.layers[il].attn_norm, NULL,LLM_NORM_RMS, cb, il);cb(cur, "attn_norm", il);// self_attention{struct ggml_tensor * q = NULL;if (!is_lite) {// {n_embd, q_lora_rank} * {n_embd, n_tokens} -> {q_lora_rank, n_tokens}q = ggml_mul_mat(ctx0, model.layers[il].wq_a, cur);cb(q, "q", il);q = llm_build_norm(ctx0, q, hparams,model.layers[il].attn_q_a_norm, NULL,LLM_NORM_RMS, cb, il);cb(q, "q", il);// {q_lora_rank, n_head * hparams.n_embd_head_k} * {q_lora_rank, n_tokens} -> {n_head * hparams.n_embd_head_k, n_tokens}q = ggml_mul_mat(ctx0, model.layers[il].wq_b, q);cb(q, "q", il);} else {q = ggml_mul_mat(ctx0, model.layers[il].wq, cur);cb(q, "q", il);}// split into {n_head * n_embd_head_qk_nope, n_tokens}struct ggml_tensor * q_nope = ggml_view_3d(ctx0, q, n_embd_head_qk_nope, n_head, n_tokens,ggml_row_size(q->type, hparams.n_embd_head_k),ggml_row_size(q->type, hparams.n_embd_head_k * n_head),0);cb(q_nope, "q_nope", il);// and {n_head * n_embd_head_qk_rope, n_tokens}struct ggml_tensor * q_pe = ggml_view_3d(ctx0, q, n_embd_head_qk_rope, n_head, n_tokens,ggml_row_size(q->type, hparams.n_embd_head_k),ggml_row_size(q->type, hparams.n_embd_head_k * n_head),ggml_row_size(q->type, n_embd_head_qk_nope));cb(q_pe, "q_pe", il);// {n_embd, kv_lora_rank + n_embd_head_qk_rope} * {n_embd, n_tokens} -> {kv_lora_rank + n_embd_head_qk_rope, n_tokens}struct ggml_tensor * kv_pe_compresseed = ggml_mul_mat(ctx0, model.layers[il].wkv_a_mqa, cur);cb(kv_pe_compresseed, "kv_pe_compresseed", il);// split into {kv_lora_rank, n_tokens}struct ggml_tensor * kv_compressed = ggml_view_2d(ctx0, kv_pe_compresseed, kv_lora_rank, n_tokens,kv_pe_compresseed->nb[1],0);cb(kv_compressed, "kv_compressed", il);// and {n_embd_head_qk_rope, n_tokens}struct ggml_tensor * k_pe = ggml_view_3d(ctx0, kv_pe_compresseed, n_embd_head_qk_rope, 1, n_tokens,kv_pe_compresseed->nb[1],kv_pe_compresseed->nb[1],ggml_row_size(kv_pe_compresseed->type, kv_lora_rank));cb(k_pe, "k_pe", il);kv_compressed = ggml_cont(ctx0, kv_compressed); // TODO: the CUDA backend does not support non-contiguous normkv_compressed = llm_build_norm(ctx0, kv_compressed, hparams,model.layers[il].attn_kv_a_norm, NULL,LLM_NORM_RMS, cb, il);cb(kv_compressed, "kv_compressed", il);// {kv_lora_rank, n_head * (n_embd_head_qk_nope + n_embd_head_v)} * {kv_lora_rank, n_tokens} -> {n_head * (n_embd_head_qk_nope + n_embd_head_v), n_tokens}struct ggml_tensor * kv = ggml_mul_mat(ctx0, model.layers[il].wkv_b, kv_compressed);cb(kv, "kv", il);// split into {n_head * n_embd_head_qk_nope, n_tokens}struct ggml_tensor * k_nope = ggml_view_3d(ctx0, kv, n_embd_head_qk_nope, n_head, n_tokens,ggml_row_size(kv->type, n_embd_head_qk_nope + hparams.n_embd_head_v),ggml_row_size(kv->type, n_head * (n_embd_head_qk_nope + hparams.n_embd_head_v)),0);cb(k_nope, "k_nope", il);// and {n_head * n_embd_head_v, n_tokens}struct ggml_tensor * v_states = ggml_view_3d(ctx0, kv, hparams.n_embd_head_v, n_head, n_tokens,ggml_row_size(kv->type, (n_embd_head_qk_nope + hparams.n_embd_head_v)),ggml_row_size(kv->type, (n_embd_head_qk_nope + hparams.n_embd_head_v)*n_head),ggml_row_size(kv->type, (n_embd_head_qk_nope)));cb(v_states, "v_states", il);v_states = ggml_cont(ctx0, v_states);cb(v_states, "v_states", il);v_states = ggml_view_2d(ctx0, v_states, hparams.n_embd_head_v * n_head, n_tokens,ggml_row_size(kv->type, hparams.n_embd_head_v * n_head),0);cb(v_states, "v_states", il);q_pe = ggml_cont(ctx0, q_pe); // TODO: the CUDA backend used to not support non-cont. RoPE, investigate removing thisq_pe = ggml_rope_ext(ctx0, q_pe, inp_pos, nullptr,n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,ext_factor, attn_factor_scaled, beta_fast, beta_slow);cb(q_pe, "q_pe", il);// shared RoPE keyk_pe = ggml_cont(ctx0, k_pe); // TODO: the CUDA backend used to not support non-cont. RoPE, investigate removing thisk_pe = ggml_rope_ext(ctx0, k_pe, inp_pos, nullptr,n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,ext_factor, attn_factor_scaled, beta_fast, beta_slow);cb(k_pe, "k_pe", il);struct ggml_tensor * q_states = ggml_concat(ctx0, q_nope, q_pe, 0);cb(q_states, "q_states", il);struct ggml_tensor * k_states = ggml_concat(ctx0, k_nope, ggml_repeat(ctx0, k_pe, q_pe), 0);cb(k_states, "k_states", il);cur = llm_build_kv(ctx0, lctx, kv_self, gf,model.layers[il].wo, NULL,k_states, v_states, q_states, KQ_mask, n_tokens, kv_head, n_kv, kq_scale, cb, il);}if (il == n_layer - 1) {// skip computing output for unused tokensstruct ggml_tensor * inp_out_ids = build_inp_out_ids();n_tokens = n_outputs;cur = ggml_get_rows(ctx0, cur, inp_out_ids);inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);}struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);cb(ffn_inp, "ffn_inp", il);cur = llm_build_norm(ctx0, ffn_inp, hparams,model.layers[il].ffn_norm, NULL,LLM_NORM_RMS, cb, il);cb(cur, "ffn_norm", il);if ((uint32_t) il < hparams.n_layer_dense_lead) {cur = llm_build_ffn(ctx0, lctx, cur,model.layers[il].ffn_up, NULL, NULL,model.layers[il].ffn_gate, NULL, NULL,model.layers[il].ffn_down, NULL, NULL,NULL,LLM_FFN_SILU, LLM_FFN_PAR, cb, il);cb(cur, "ffn_out", il);} else {// MoE branchggml_tensor * moe_out =llm_build_moe_ffn(ctx0, lctx, cur,model.layers[il].ffn_gate_inp,model.layers[il].ffn_up_exps,model.layers[il].ffn_gate_exps,model.layers[il].ffn_down_exps,model.layers[il].ffn_exp_probs_b,n_expert, n_expert_used,LLM_FFN_SILU, hparams.expert_weights_norm,true, hparams.expert_weights_scale,(enum llama_expert_gating_func_type) hparams.expert_gating_func,cb, il);cb(moe_out, "ffn_moe_out", il);// FFN shared expert{ggml_tensor * ffn_shexp = llm_build_ffn(ctx0, lctx, cur,model.layers[il].ffn_up_shexp, NULL, NULL,model.layers[il].ffn_gate_shexp, NULL, NULL,model.layers[il].ffn_down_shexp, NULL, NULL,NULL,LLM_FFN_SILU, LLM_FFN_PAR, cb, il);cb(ffn_shexp, "ffn_shexp", il);cur = ggml_add(ctx0, moe_out, ffn_shexp);cb(cur, "ffn_out", il);}}cur = ggml_add(ctx0, cur, ffn_inp);cur = lctx.cvec.apply_to(ctx0, cur, il);cb(cur, "l_out", il);// input for next layerinpL = cur;}cur = inpL;cur = llm_build_norm(ctx0, cur, hparams,model.output_norm, NULL,LLM_NORM_RMS, cb, -1);cb(cur, "result_norm", -1);// lm_headcur = ggml_mul_mat(ctx0, model.output, cur);cb(cur, "result_output", -1);ggml_build_forward_expand(gf, cur);return gf;}
case LLM_ARCH_DEEPSEEK:andcase LLM_ARCH_DEEPSEEK2:
switch (model.arch) {case LLM_ARCH_LLAMA:case LLM_ARCH_MINICPM:case LLM_ARCH_GRANITE:case LLM_ARCH_GRANITE_MOE:{result = llm.build_llama();} break;case LLM_ARCH_DECI:{result = llm.build_deci();} break;case LLM_ARCH_BAICHUAN:{result = llm.build_baichuan();} break;case LLM_ARCH_FALCON:{result = llm.build_falcon();} break;case LLM_ARCH_GROK:{result = llm.build_grok();} break;case LLM_ARCH_STARCODER:{result = llm.build_starcoder();} break;case LLM_ARCH_REFACT:{result = llm.build_refact();} break;case LLM_ARCH_BERT:case LLM_ARCH_JINA_BERT_V2:case LLM_ARCH_NOMIC_BERT:{result = llm.build_bert();} break;case LLM_ARCH_BLOOM:{result = llm.build_bloom();} break;case LLM_ARCH_MPT:{result = llm.build_mpt();} break;case LLM_ARCH_STABLELM:{result = llm.build_stablelm();} break;case LLM_ARCH_QWEN:{result = llm.build_qwen();} break;case LLM_ARCH_QWEN2:{result = llm.build_qwen2();} break;case LLM_ARCH_QWEN2VL:{lctx.n_pos_per_token = 4;result = llm.build_qwen2vl();} break;case LLM_ARCH_QWEN2MOE:{result = llm.build_qwen2moe();} break;case LLM_ARCH_PHI2:{result = llm.build_phi2();} break;case LLM_ARCH_PHI3:case LLM_ARCH_PHIMOE:{result = llm.build_phi3();} break;case LLM_ARCH_PLAMO:{result = llm.build_plamo();} break;case LLM_ARCH_GPT2:{result = llm.build_gpt2();} break;case LLM_ARCH_CODESHELL:{result = llm.build_codeshell();} break;case LLM_ARCH_ORION:{result = llm.build_orion();} break;case LLM_ARCH_INTERNLM2:{result = llm.build_internlm2();} break;case LLM_ARCH_MINICPM3:{result = llm.build_minicpm3();} break;case LLM_ARCH_GEMMA:{result = llm.build_gemma();} break;case LLM_ARCH_GEMMA2:{result = llm.build_gemma2();} break;case LLM_ARCH_STARCODER2:{result = llm.build_starcoder2();} break;case LLM_ARCH_MAMBA:{result = llm.build_mamba();} break;case LLM_ARCH_XVERSE:{result = llm.build_xverse();} break;case LLM_ARCH_COMMAND_R:{result = llm.build_command_r();} break;case LLM_ARCH_COHERE2:{result = llm.build_cohere2();} break;case LLM_ARCH_DBRX:{result = llm.build_dbrx();} break;case LLM_ARCH_OLMO:{result = llm.build_olmo();} break;case LLM_ARCH_OLMO2:{result = llm.build_olmo2();} break;case LLM_ARCH_OLMOE:{result = llm.build_olmoe();} break;case LLM_ARCH_OPENELM:{result = llm.build_openelm();} break;case LLM_ARCH_GPTNEOX:{result = llm.build_gptneox();} break;case LLM_ARCH_ARCTIC:{result = llm.build_arctic();} break;case LLM_ARCH_DEEPSEEK:{result = llm.build_deepseek();} break;case LLM_ARCH_DEEPSEEK2:{result = llm.build_deepseek2();} break;case LLM_ARCH_CHATGLM:{result = llm.build_chatglm();} break;case LLM_ARCH_BITNET:{result = llm.build_bitnet();} break;case LLM_ARCH_T5:{if (lctx.is_encoding) {result = llm.build_t5_enc();} else {result = llm.build_t5_dec();}} break;case LLM_ARCH_T5ENCODER:{result = llm.build_t5_enc();} break;case LLM_ARCH_JAIS:{result = llm.build_jais();} break;case LLM_ARCH_NEMOTRON:{result = llm.build_nemotron();} break;case LLM_ARCH_EXAONE:{result = llm.build_exaone();} break;case LLM_ARCH_RWKV6:{result = llm.build_rwkv6();} break;case LLM_ARCH_RWKV6QWEN2:{result = llm.build_rwkv6qwen2();} break;case LLM_ARCH_CHAMELEON:{result = llm.build_chameleon();} break;case LLM_ARCH_WAVTOKENIZER_DEC:{result = llm.build_wavtokenizer_dec();} break;default:GGML_ABORT("fatal error");}
References
[1] Yongqiang Cheng, https://yongqiang.blog.csdn.net/
[2] huggingface/gguf, https://github.com/huggingface/huggingface.js/tree/main/packages/gguf
———MP3文件格式解读)
