model: Add support for PhiMoE arch (#11003)
* model: support phimoe * python linter * doc: minor Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com> * doc: minor Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com> * doc: add phimoe as supported model ggml-ci --------- Co-authored-by: ThiloteE <73715071+ThiloteE@users.noreply.github.com>
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Pierrick Hymbert
GitHub
parent
be0e950c91
commit
f8feb4b01a
10 changed files with 208 additions and 31 deletions
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@ -244,6 +244,7 @@ class MODEL_ARCH(IntEnum):
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QWEN2VL = auto()
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PHI2 = auto()
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PHI3 = auto()
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PHIMOE = auto()
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PLAMO = auto()
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CODESHELL = auto()
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ORION = auto()
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@ -428,6 +429,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
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MODEL_ARCH.QWEN2VL: "qwen2vl",
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MODEL_ARCH.PHI2: "phi2",
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MODEL_ARCH.PHI3: "phi3",
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MODEL_ARCH.PHIMOE: "phimoe",
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MODEL_ARCH.PLAMO: "plamo",
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MODEL_ARCH.CODESHELL: "codeshell",
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MODEL_ARCH.ORION: "orion",
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@ -940,6 +942,24 @@ 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.PHIMOE: [
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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_FACTORS_LONG,
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MODEL_TENSOR.ROPE_FACTORS_SHORT,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_QKV,
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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.FFN_NORM,
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MODEL_TENSOR.FFN_GATE_INP,
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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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MODEL_ARCH.CODESHELL: [
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.POS_EMBD,
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@ -55,7 +55,7 @@ class TensorNameMap:
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# Output
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MODEL_TENSOR.OUTPUT: (
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"embed_out", # gptneox
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"lm_head", # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais nemotron exaone olmoe olmo2
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"lm_head", # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais nemotron exaone olmoe olmo2 phimoe
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"output", # llama-pth bloom internlm2
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"word_embeddings_for_head", # persimmon
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"lm_head.linear", # phi2
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@ -68,7 +68,7 @@ class TensorNameMap:
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MODEL_TENSOR.OUTPUT_NORM: (
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"gpt_neox.final_layer_norm", # gptneox
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"transformer.ln_f", # gpt2 gpt-j falcon jais exaone
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"model.norm", # llama-hf baichuan internlm2 olmoe olmo2
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"model.norm", # llama-hf baichuan internlm2 olmoe olmo2 phimoe
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"norm", # llama-pth
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"transformer.norm_f", # mpt dbrx
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"ln_f", # refact bloom qwen gpt2
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@ -108,7 +108,7 @@ class TensorNameMap:
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"transformer.h.{bid}.input_layernorm", # falcon7b
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"h.{bid}.input_layernorm", # bloom
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"transformer.h.{bid}.ln_mlp", # falcon40b
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"model.layers.{bid}.input_layernorm", # llama-hf nemotron olmoe
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"model.layers.{bid}.input_layernorm", # llama-hf nemotron olmoe phimoe
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"layers.{bid}.attention_norm", # llama-pth
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"language_model.encoder.layers.{bid}.input_layernorm", # persimmon
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"model.layers.{bid}.ln1", # yi
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@ -152,7 +152,7 @@ class TensorNameMap:
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# Attention query
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MODEL_TENSOR.ATTN_Q: (
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"model.layers.{bid}.self_attn.q_proj", # llama-hf nemotron olmoe olmo2
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"model.layers.{bid}.self_attn.q_proj", # llama-hf nemotron olmoe olmo2 phimoe
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"model.layers.{bid}.self_attn.q_proj_no_perm", # llama-custom
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"layers.{bid}.attention.wq", # llama-pth
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"encoder.layer.{bid}.attention.self.query", # bert
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@ -165,7 +165,7 @@ class TensorNameMap:
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# Attention key
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MODEL_TENSOR.ATTN_K: (
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"model.layers.{bid}.self_attn.k_proj", # llama-hf nemotron olmoe olmo2
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"model.layers.{bid}.self_attn.k_proj", # llama-hf nemotron olmoe olmo2 phimoe
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"model.layers.{bid}.self_attn.k_proj_no_perm", # llama-custom
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"layers.{bid}.attention.wk", # llama-pth
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"encoder.layer.{bid}.attention.self.key", # bert
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@ -179,7 +179,7 @@ class TensorNameMap:
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# Attention value
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MODEL_TENSOR.ATTN_V: (
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"model.layers.{bid}.self_attn.v_proj", # llama-hf nemotron olmoe olmo2
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"model.layers.{bid}.self_attn.v_proj", # llama-hf nemotron olmoe olmo2 phimoe
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"layers.{bid}.attention.wv", # llama-pth
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"encoder.layer.{bid}.attention.self.value", # bert
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"transformer.h.{bid}.attn.v_proj", # gpt-j
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@ -197,7 +197,7 @@ class TensorNameMap:
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"transformer.blocks.{bid}.attn.out_proj", # mpt
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"transformer.h.{bid}.self_attention.dense", # falcon
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"h.{bid}.self_attention.dense", # bloom
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"model.layers.{bid}.self_attn.o_proj", # llama-hf nemotron olmoe olmo2
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"model.layers.{bid}.self_attn.o_proj", # llama-hf nemotron olmoe olmo2 phimoe
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"model.layers.{bid}.self_attn.linear_attn", # deci
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"layers.{bid}.attention.wo", # llama-pth
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"encoder.layer.{bid}.attention.output.dense", # bert
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@ -242,7 +242,7 @@ class TensorNameMap:
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"transformer.h.{bid}.ln_2", # gpt2 refact qwen jais exaone
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"h.{bid}.post_attention_layernorm", # bloom
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"transformer.blocks.{bid}.norm_2", # mpt
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"model.layers.{bid}.post_attention_layernorm", # llama-hf nemotron olmoe
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"model.layers.{bid}.post_attention_layernorm", # llama-hf nemotron olmoe phimoe
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"layers.{bid}.ffn_norm", # llama-pth
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"language_model.encoder.layers.{bid}.post_attention_layernorm", # persimmon
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"model.layers.{bid}.ln2", # yi
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@ -265,7 +265,7 @@ class TensorNameMap:
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MODEL_TENSOR.FFN_GATE_INP: (
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"layers.{bid}.feed_forward.gate", # mixtral
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"model.layers.{bid}.block_sparse_moe.gate", # mixtral
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"model.layers.{bid}.block_sparse_moe.gate", # mixtral phimoe
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"model.layers.{bid}.mlp.gate", # qwen2moe olmoe
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"transformer.decoder_layer.{bid}.router", # Grok
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"transformer.blocks.{bid}.ffn.router.layer", # dbrx
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@ -310,10 +310,11 @@ class TensorNameMap:
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),
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MODEL_TENSOR.FFN_UP_EXP: (
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"layers.{bid}.feed_forward.experts.w3", # mixtral (merged)
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"transformer.decoder_layer.{bid}.moe.linear_v", # Grok (merged)
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"transformer.blocks.{bid}.ffn.experts.mlp.v1", # dbrx
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"model.layers.{bid}.mlp.experts.up_proj", # qwen2moe olmoe (merged)
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"layers.{bid}.feed_forward.experts.w3", # mixtral (merged)
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"transformer.decoder_layer.{bid}.moe.linear_v", # Grok (merged)
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"transformer.blocks.{bid}.ffn.experts.mlp.v1", # dbrx
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"model.layers.{bid}.mlp.experts.up_proj", # qwen2moe olmoe (merged)
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"model.layers.{bid}.block_sparse_moe.experts.w3", # phimoe (merged)
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),
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MODEL_TENSOR.FFN_UP_SHEXP: (
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@ -342,10 +343,11 @@ class TensorNameMap:
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),
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MODEL_TENSOR.FFN_GATE_EXP: (
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"layers.{bid}.feed_forward.experts.w1", # mixtral (merged)
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"transformer.decoder_layer.{bid}.moe.linear", # Grok (merged)
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"transformer.blocks.{bid}.ffn.experts.mlp.w1", # dbrx
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"model.layers.{bid}.mlp.experts.gate_proj", # qwen2moe olmoe (merged)
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"layers.{bid}.feed_forward.experts.w1", # mixtral (merged)
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"transformer.decoder_layer.{bid}.moe.linear", # Grok (merged)
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"transformer.blocks.{bid}.ffn.experts.mlp.w1", # dbrx
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"model.layers.{bid}.mlp.experts.gate_proj", # qwen2moe olmoe (merged)
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"model.layers.{bid}.block_sparse_moe.experts.w1", # phimoe (merged)
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),
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MODEL_TENSOR.FFN_GATE_SHEXP: (
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@ -387,6 +389,7 @@ class TensorNameMap:
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"transformer.blocks.{bid}.ffn.experts.mlp.w2", # dbrx
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"model.layers.{bid}.mlp.experts.down_proj", # qwen2moe olmoe (merged)
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"model.layers.{bid}.block_sparse_moe.output_linear", # granitemoe
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"model.layers.{bid}.block_sparse_moe.experts.w2", # phimoe (merged)
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),
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MODEL_TENSOR.FFN_DOWN_SHEXP: (
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