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convert : proper tensor name mapping for llama4 (#12870)

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* Llama-4 mapping

* remove hacky renaming

---------

Co-authored-by: Daniel Han <danielhanchen@gmail.com>
This commit is contained in:
Xuan-Son Nguyen 2025-04-11 09:23:37 +02:00 committed by GitHub
parent 8b91d5355a
commit 5b1f13cb64
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2 changed files with 19 additions and 4 deletions
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4
convert_hf_to_gguf.py
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@ -1806,10 +1806,6 @@ class Llama4Model(LlamaModel):
self.gguf_writer.add_expert_feed_forward_length(self.hparams["intermediate_size_moe"])
def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):
name = name.replace("language_model.", "")
name = name.replace("feed_forward.", "mlp.") # a bit hacky for now
name = name.replace(".router.weight", ".gate.weight") # a bit hacky for now
# split the gate_up into gate and up
if "gate_up_proj" in name:
name_up = name.replace("gate_up_proj", "up_proj.weight")

19
gguf-py/gguf/tensor_mapping.py
View File

@ -30,6 +30,7 @@ class TensorNameMap:
"rwkv.embeddings", # rwkv6
"model.embeddings", # rwkv7
"model.word_embeddings", # bailingmoe
"language_model.model.embed_tokens", # llama4
),
# Token type embeddings
@ -67,6 +68,7 @@ class TensorNameMap:
"output_layer", # chatglm
"head", # rwkv
"head.out", # wavtokenizer
"language_model.lm_head", # llama4
),
# Output norm
@ -89,6 +91,7 @@ class TensorNameMap:
"rwkv.ln_out", # rwkv6
"model.ln_out", # rwkv7
"backbone.final_layer_norm", # wavtokenizer
"language_model.model.norm", # llama4
),
# Rope frequencies
@ -130,6 +133,7 @@ class TensorNameMap:
"transformer.layers.{bid}.attn_norm", # openelm
"rwkv.blocks.{bid}.ln1", # rwkv6
"model.layers.{bid}.ln1", # rwkv7
"language_model.model.layers.{bid}.input_layernorm", # llama4
),
# Attention norm 2
@ -169,6 +173,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wq", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.query",# Grok
"transformer.h.{bid}.attn.attention.q_proj", # exaone
"language_model.model.layers.{bid}.self_attn.q_proj", # llama4
),
# Attention key
@ -183,6 +188,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wk", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.key",# Grok
"transformer.h.{bid}.attn.attention.k_proj", # exaone
"language_model.model.layers.{bid}.self_attn.k_proj", # llama4
),
# Attention value
@ -196,6 +202,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wv", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.value",# Grok
"transformer.h.{bid}.attn.attention.v_proj", # exaone
"language_model.model.layers.{bid}.self_attn.v_proj", # llama4
),
# Attention output
@ -222,6 +229,7 @@ class TensorNameMap:
"encoder.layers.{bid}.self_attention.dense", # chatglm
"transformer.layers.{bid}.attn.out_proj", # openelm
"transformer.h.{bid}.attn.attention.out_proj", # exaone
"language_model.model.layers.{bid}.self_attn.o_proj", # llama4
),
# Attention output norm
@ -259,6 +267,7 @@ class TensorNameMap:
"transformer.decoder_layer.{bid}.rms_norm_2", # Grok
"encoder.layers.{bid}.post_attention_layernorm", # chatglm
"transformer.layers.{bid}.ffn_norm", # openelm
"language_model.model.layers.{bid}.post_attention_layernorm", # llama4
),
# Post feed-forward norm
@ -278,6 +287,7 @@ class TensorNameMap:
"transformer.decoder_layer.{bid}.router", # Grok
"transformer.blocks.{bid}.ffn.router.layer", # dbrx
"model.layers.{bid}.block_sparse_moe.router.layer", # granitemoe
"language_model.model.layers.{bid}.feed_forward.router", # llama4
),
MODEL_TENSOR.FFN_GATE_INP_SHEXP: (
@ -315,6 +325,7 @@ class TensorNameMap:
"model.layers.{bid}.residual_mlp.w3", # arctic
"encoder.layers.{bid}.mlp.dense_h_to_4h", # chatglm
"transformer.h.{bid}.mlp.c_fc_1", # exaone
"language_model.model.layers.{bid}.feed_forward.up_proj", # llama4
),
MODEL_TENSOR.FFN_UP_EXP: (
@ -323,11 +334,13 @@ class TensorNameMap:
"transformer.blocks.{bid}.ffn.experts.mlp.v1", # dbrx
"model.layers.{bid}.mlp.experts.up_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.experts.w3", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.up_proj", # llama4
),
MODEL_TENSOR.FFN_UP_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.up_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.up_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.up_proj", # llama4
),
# AWQ-activation gate
@ -348,6 +361,7 @@ class TensorNameMap:
"transformer.h.{bid}.mlp.linear_1", # refact
"model.layers.{bid}.residual_mlp.w1", # arctic
"transformer.h.{bid}.mlp.c_fc_0", # exaone
"language_model.model.layers.{bid}.feed_forward.gate_proj", # llama4
),
MODEL_TENSOR.FFN_GATE_EXP: (
@ -356,11 +370,13 @@ class TensorNameMap:
"transformer.blocks.{bid}.ffn.experts.mlp.w1", # dbrx
"model.layers.{bid}.mlp.experts.gate_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.experts.w1", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.gate_proj", # llama4
),
MODEL_TENSOR.FFN_GATE_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.gate_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.gate_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.gate_proj", # llama4
),
# Feed-forward down
@ -389,6 +405,7 @@ class TensorNameMap:
"encoder.layer.{bid}.mlp.down_layer", # jina-bert-v2
"encoder.layers.{bid}.mlp.dense_4h_to_h", # chatglm
"model.layers.h.{bid}.mlp.c_proj", # exaone
"language_model.model.layers.{bid}.feed_forward.down_proj", # llama4
),
MODEL_TENSOR.FFN_DOWN_EXP: (
@ -398,11 +415,13 @@ class TensorNameMap:
"model.layers.{bid}.mlp.experts.down_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.output_linear", # granitemoe
"model.layers.{bid}.block_sparse_moe.experts.w2", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.down_proj", # llama4
),
MODEL_TENSOR.FFN_DOWN_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.down_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.down_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.down_proj", # llama4
),
MODEL_TENSOR.ATTN_Q_NORM: (