vbatts/llama.cpp
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llama: Add support for Gemma2ForCausalLM (#8156)

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* Inference support for Gemma 2 model family

* Update convert-hf-to-gguf.py, constants, and tensor mappings

* cleanup

* format fix

* Fix special token vocab bug

* Don't add space prefix

* fix deleted lines

* Update src/llama.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* Add model type names

* Add control vector

* Fix model type identification

---------

Co-authored-by: Andrei Betlen <abetlen@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
pculliton 2024-06-28 00:00:43 -04:00 • committed by GitHub
parent a27aa50ab7
commit e57dc62057
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4 changed files with 274 additions and 1 deletions
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23
gguf-py/gguf/constants.py
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@ -150,6 +150,7 @@ class MODEL_ARCH(IntEnum):
INTERNLM2 = auto()
MINICPM = auto()
GEMMA = auto()
GEMMA2 = auto()
STARCODER2 = auto()
MAMBA = auto()
XVERSE = auto()
@ -180,10 +181,13 @@ class MODEL_TENSOR(IntEnum):
ATTN_NORM = auto()
ATTN_NORM_2 = auto()
ATTN_OUT_NORM = auto()
ATTN_POST_NORM = auto()
ATTN_ROT_EMBD = auto()
FFN_GATE_INP = auto()
FFN_GATE_INP_SHEXP = auto()
FFN_NORM = auto()
FFN_PRE_NORM = auto()
FFN_POST_NORM = auto()
FFN_GATE = auto()
FFN_DOWN = auto()
FFN_UP = auto()
@ -270,6 +274,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
MODEL_ARCH.INTERNLM2: "internlm2",
MODEL_ARCH.MINICPM: "minicpm",
MODEL_ARCH.GEMMA: "gemma",
MODEL_ARCH.GEMMA2: "gemma2",
MODEL_ARCH.STARCODER2: "starcoder2",
MODEL_ARCH.MAMBA: "mamba",
MODEL_ARCH.XVERSE: "xverse",
@ -303,9 +308,12 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
MODEL_TENSOR.ATTN_Q_NORM: "blk.{bid}.attn_q_norm",
MODEL_TENSOR.ATTN_K_NORM: "blk.{bid}.attn_k_norm",
MODEL_TENSOR.ATTN_OUT_NORM: "blk.{bid}.attn_output_norm",
MODEL_TENSOR.ATTN_POST_NORM: "blk.{bid}.post_attention_norm",
MODEL_TENSOR.FFN_GATE_INP: "blk.{bid}.ffn_gate_inp",
MODEL_TENSOR.FFN_GATE_INP_SHEXP: "blk.{bid}.ffn_gate_inp_shexp",
MODEL_TENSOR.FFN_NORM: "blk.{bid}.ffn_norm",
MODEL_TENSOR.FFN_PRE_NORM: "blk.{bid}.ffn_norm",
MODEL_TENSOR.FFN_POST_NORM: "blk.{bid}.post_ffw_norm",
MODEL_TENSOR.FFN_GATE: "blk.{bid}.ffn_gate",
MODEL_TENSOR.FFN_DOWN: "blk.{bid}.ffn_down",
MODEL_TENSOR.FFN_UP: "blk.{bid}.ffn_up",
@ -751,6 +759,21 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.FFN_UP,
MODEL_TENSOR.FFN_NORM,
],
MODEL_ARCH.GEMMA2: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_V,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_UP,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_POST_NORM,
MODEL_TENSOR.FFN_PRE_NORM,
MODEL_TENSOR.FFN_POST_NORM,
],
MODEL_ARCH.STARCODER2: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,

14
gguf-py/gguf/tensor_mapping.py
View file

@ -187,6 +187,10 @@ class TensorNameMap:
"transformer.blocks.{bid}.norm_attn_norm.norm_2", # dbrx
),
MODEL_TENSOR.ATTN_POST_NORM: (
"model.layers.{bid}.post_attention_layernorm", # gemma2
),
# Rotary embeddings
MODEL_TENSOR.ATTN_ROT_EMBD: (
"model.layers.{bid}.self_attn.rotary_emb.inv_freq", # llama-hf
@ -210,6 +214,16 @@ class TensorNameMap:
"transformer.decoder_layer.{bid}.rms_norm_2", # Grok
),
# Post feed-forward norm
MODEL_TENSOR.FFN_PRE_NORM: (
"model.layers.{bid}.pre_feedforward_layernorm", # gemma2
),
# Post feed-forward norm
MODEL_TENSOR.FFN_POST_NORM: (
"model.layers.{bid}.post_feedforward_layernorm", # gemma2
),
MODEL_TENSOR.FFN_GATE_INP: (
"layers.{bid}.feed_forward.gate", # mixtral
"model.layers.{bid}.block_sparse_moe.gate", # mixtral