vbatts/llama.cpp
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Add support for ArcticForCausalLM (#7020)

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* 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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fairydreaming 2024-05-24 14:31:13 +02:00 • committed by GitHub
parent 0df0aa8e43
commit fbca2f27fc
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4 changed files with 456 additions and 43 deletions
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19
gguf-py/gguf/tensor_mapping.py
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@ -244,6 +244,7 @@ class TensorNameMap:
"encoder.layers.{bid}.mlp.fc11", # nomic-bert
"model.layers.{bid}.mlp.c_fc", # starcoder2
"encoder.layer.{bid}.mlp.gated_layers_v", # jina-bert-v2
"model.layers.{bid}.residual_mlp.w3", # arctic
),
MODEL_TENSOR.FFN_UP_EXP: (
@ -272,6 +273,7 @@ class TensorNameMap:
"encoder.layers.{bid}.mlp.fc12", # nomic-bert
"encoder.layer.{bid}.mlp.gated_layers_w", # jina-bert-v2
"transformer.h.{bid}.mlp.linear_1", # refact
"model.layers.{bid}.residual_mlp.w1", # arctic
),
MODEL_TENSOR.FFN_GATE_EXP: (
@ -306,6 +308,7 @@ class TensorNameMap:
"encoder.layers.{bid}.mlp.fc2", # nomic-bert
"model.layers.{bid}.mlp.c_proj", # starcoder2
"encoder.layer.{bid}.mlp.wo", # jina-bert-v2
"model.layers.{bid}.residual_mlp.w2", # arctic
),
MODEL_TENSOR.FFN_DOWN_EXP: (
@ -382,6 +385,18 @@ class TensorNameMap:
),
}
# architecture-specific block mappings
arch_block_mappings_cfg: dict[MODEL_ARCH, dict[MODEL_TENSOR, tuple[str, ...]]] = {
MODEL_ARCH.ARCTIC: {
MODEL_TENSOR.FFN_NORM: (
"model.layers.{bid}.residual_layernorm",
),
MODEL_TENSOR.FFN_NORM_EXP: (
"model.layers.{bid}.post_attention_layernorm",
),
},
}
mapping: dict[str, tuple[MODEL_TENSOR, str]]
def __init__(self, arch: MODEL_ARCH, n_blocks: int):
@ -393,12 +408,14 @@ class TensorNameMap:
self.mapping[tensor_name] = (tensor, tensor_name)
for key in keys:
self.mapping[key] = (tensor, tensor_name)
if arch in self.arch_block_mappings_cfg:
self.block_mappings_cfg.update(self.arch_block_mappings_cfg[arch])
for bid in range(n_blocks):
for tensor, keys in self.block_mappings_cfg.items():
if tensor not in MODEL_TENSORS[arch]:
continue
# TODO: make this configurable
n_experts = 60
n_experts = 128
for xid in range(n_experts):
tensor_name = TENSOR_NAMES[tensor].format(bid = bid, xid = xid)
self.mapping[tensor_name] = (tensor, tensor_name)