vbatts/llama.cpp
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llm : add Refact model (#3329)

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* add refact model

* resolve comments

* rebase to the latest

* solve alibi cpu error

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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ds5t5 2023-10-04 06:23:39 -07:00 • committed by GitHub
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4 changed files with 723 additions and 10 deletions
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gguf-py/gguf/gguf.py
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@ -85,6 +85,7 @@ class MODEL_ARCH(IntEnum):
GPTNEOX : int = auto()
MPT : int = auto()
STARCODER : int = auto()
REFACT : int = auto()
BERT : int = auto()
@ -118,6 +119,7 @@ MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
MODEL_ARCH.GPTNEOX: "gptneox",
MODEL_ARCH.MPT: "mpt",
MODEL_ARCH.STARCODER: "starcoder",
MODEL_ARCH.REFACT: "refact",
MODEL_ARCH.BERT: "bert",
}
@ -247,6 +249,20 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_UP,
],
MODEL_ARCH.REFACT: [
MODEL_TENSOR.TOKEN_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.OUTPUT,
MODEL_TENSOR.ATTN_NORM,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_V,
MODEL_TENSOR.ATTN_OUT,
MODEL_TENSOR.FFN_NORM,
MODEL_TENSOR.FFN_GATE,
MODEL_TENSOR.FFN_DOWN,
MODEL_TENSOR.FFN_UP,
],
MODEL_ARCH.GPT2: [
# TODO
],
@ -271,7 +287,7 @@ class TensorNameMap:
# Token embeddings
MODEL_TENSOR.TOKEN_EMBD: (
"gpt_neox.embed_in", # gptneox
"transformer.wte", # gpt2 gpt-j mpt
"transformer.wte", # gpt2 gpt-j mpt refact
"transformer.word_embeddings", # falcon
"model.embed_tokens", # llama-hf
"tok_embeddings", # llama-pth
@ -304,6 +320,7 @@ class TensorNameMap:
"norm", # llama-pth
"embeddings.LayerNorm", # bert
"transformer.norm_f", # mpt
"ln_f", # refact
),
# Rope frequencies
@ -316,7 +333,7 @@ class TensorNameMap:
# Attention norm
MODEL_TENSOR.ATTN_NORM: (
"gpt_neox.layers.{bid}.input_layernorm", # gptneox
"transformer.h.{bid}.ln_1", # gpt2 gpt-j
"transformer.h.{bid}.ln_1", # gpt2 gpt-j refact
"transformer.blocks.{bid}.norm_1", # mpt
"transformer.h.{bid}.input_layernorm", # falcon7b
"transformer.h.{bid}.ln_mlp", # falcon40b
@ -365,7 +382,7 @@ class TensorNameMap:
# Attention output
MODEL_TENSOR.ATTN_OUT: (
"gpt_neox.layers.{bid}.attention.dense", # gptneox
"transformer.h.{bid}.attn.c_proj", # gpt2
"transformer.h.{bid}.attn.c_proj", # gpt2 refact
"transformer.blocks.{bid}.attn.out_proj", # mpt
"transformer.h.{bid}.self_attention.dense", # falcon
"model.layers.{bid}.self_attn.o_proj", # llama-hf
@ -383,7 +400,7 @@ class TensorNameMap:
# Feed-forward norm
MODEL_TENSOR.FFN_NORM: (
"gpt_neox.layers.{bid}.post_attention_layernorm", # gptneox
"transformer.h.{bid}.ln_2", # gpt2
"transformer.h.{bid}.ln_2", # gpt2 refact
"transformer.blocks.{bid}.norm_2", # mpt
"model.layers.{bid}.post_attention_layernorm", # llama-hf
"layers.{bid}.ffn_norm", # llama-pth
@ -396,7 +413,7 @@ class TensorNameMap:
"transformer.h.{bid}.mlp.c_fc", # gpt2
"transformer.blocks.{bid}.ffn.up_proj", # mpt
"transformer.h.{bid}.mlp.dense_h_to_4h", # falcon
"model.layers.{bid}.mlp.up_proj", # llama-hf
"model.layers.{bid}.mlp.up_proj", # llama-hf refact
"layers.{bid}.feed_forward.w3", # llama-pth
"encoder.layer.{bid}.intermediate.dense", # bert
"transformer.h.{bid}.mlp.fc_in", # gpt-j
@ -404,14 +421,14 @@ class TensorNameMap:
# Feed-forward gate
MODEL_TENSOR.FFN_GATE: (
"model.layers.{bid}.mlp.gate_proj", # llama-hf
"model.layers.{bid}.mlp.gate_proj", # llama-hf refact
"layers.{bid}.feed_forward.w1", # llama-pth
),
# Feed-forward down
MODEL_TENSOR.FFN_DOWN: (
"gpt_neox.layers.{bid}.mlp.dense_4h_to_h", # gptneox
"transformer.h.{bid}.mlp.c_proj", # gpt2
"transformer.h.{bid}.mlp.c_proj", # gpt2 refact
"transformer.blocks.{bid}.ffn.down_proj", # mpt
"transformer.h.{bid}.mlp.dense_4h_to_h", # falcon
"model.layers.{bid}.mlp.down_proj", # llama-hf