Add support for ArcticForCausalLM (#7020)
* common : increase max number of experts to 128 * common : add tensor LLM_TENSOR_FFN_NORM_EXPS for normalization before MoE that runs in parallel to attention + ffn * gguf-py : add architecture-specific block mappings that override selected general block mappings * convert-hf : add model conversion support for ArcticForCausalLM * convert-hf : use added_tokens_decoder from tokenizer_config.json to redefine tokens from SentencePiece model (only for ArcticForCausalLM) * llama : add inference support for LLM_ARCH_ARCTIC --------- Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
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4 changed files with 456 additions and 43 deletions
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@ -139,6 +139,7 @@ class MODEL_ARCH(IntEnum):
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COMMAND_R = auto()
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DBRX = auto()
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OLMO = auto()
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ARCTIC = auto()
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class MODEL_TENSOR(IntEnum):
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@ -167,6 +168,7 @@ class MODEL_TENSOR(IntEnum):
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FFN_DOWN = auto()
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FFN_UP = auto()
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FFN_ACT = auto()
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FFN_NORM_EXP = auto()
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FFN_GATE_EXP = auto()
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FFN_DOWN_EXP = auto()
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FFN_UP_EXP = auto()
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@ -218,6 +220,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
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MODEL_ARCH.COMMAND_R: "command-r",
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MODEL_ARCH.DBRX: "dbrx",
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MODEL_ARCH.OLMO: "olmo",
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MODEL_ARCH.ARCTIC: "arctic",
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}
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TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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@ -251,6 +254,7 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
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MODEL_TENSOR.FFN_DOWN_SHEXP: "blk.{bid}.ffn_down_shexp",
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MODEL_TENSOR.FFN_UP_SHEXP: "blk.{bid}.ffn_up_shexp",
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MODEL_TENSOR.FFN_ACT: "blk.{bid}.ffn",
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MODEL_TENSOR.FFN_NORM_EXP: "blk.{bid}.ffn_norm_exps",
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MODEL_TENSOR.FFN_GATE_EXP: "blk.{bid}.ffn_gate_exps",
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MODEL_TENSOR.FFN_DOWN_EXP: "blk.{bid}.ffn_down_exps",
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MODEL_TENSOR.FFN_UP_EXP: "blk.{bid}.ffn_up_exps",
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@ -732,6 +736,27 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
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MODEL_TENSOR.FFN_DOWN,
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MODEL_TENSOR.FFN_UP,
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],
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MODEL_ARCH.ARCTIC: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.ROPE_FREQS,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_Q,
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MODEL_TENSOR.ATTN_K,
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MODEL_TENSOR.ATTN_V,
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MODEL_TENSOR.ATTN_OUT,
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MODEL_TENSOR.ATTN_ROT_EMBD,
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MODEL_TENSOR.FFN_GATE_INP,
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MODEL_TENSOR.FFN_NORM,
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MODEL_TENSOR.FFN_GATE,
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MODEL_TENSOR.FFN_DOWN,
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MODEL_TENSOR.FFN_UP,
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MODEL_TENSOR.FFN_NORM_EXP,
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MODEL_TENSOR.FFN_GATE_EXP,
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MODEL_TENSOR.FFN_DOWN_EXP,
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MODEL_TENSOR.FFN_UP_EXP,
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],
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# TODO
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}
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