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from __future__ import annotations | |
from enum import Enum, IntEnum, auto | |
from typing import Any | |
# | |
# constants | |
# | |
GGUF_MAGIC = 0x46554747 # "GGUF" | |
GGUF_VERSION = 3 | |
GGUF_DEFAULT_ALIGNMENT = 32 | |
GGML_QUANT_VERSION = 2 # GGML_QNT_VERSION from ggml.h | |
# | |
# metadata keys | |
# | |
class Keys: | |
class General: | |
TYPE = "general.type" | |
ARCHITECTURE = "general.architecture" | |
QUANTIZATION_VERSION = "general.quantization_version" | |
ALIGNMENT = "general.alignment" | |
FILE_TYPE = "general.file_type" | |
# Authorship Metadata | |
NAME = "general.name" | |
AUTHOR = "general.author" | |
VERSION = "general.version" | |
ORGANIZATION = "general.organization" | |
FINETUNE = "general.finetune" | |
BASENAME = "general.basename" | |
DESCRIPTION = "general.description" | |
QUANTIZED_BY = "general.quantized_by" | |
SIZE_LABEL = "general.size_label" | |
# Licensing details | |
LICENSE = "general.license" | |
LICENSE_NAME = "general.license.name" | |
LICENSE_LINK = "general.license.link" | |
# Typically represents the converted GGUF repo (Unless native) | |
URL = "general.url" # Model Website/Paper | |
DOI = "general.doi" | |
UUID = "general.uuid" | |
REPO_URL = "general.repo_url" # Model Source Repository (git/svn/etc...) | |
# Model Source during conversion | |
SOURCE_URL = "general.source.url" # Model Website/Paper | |
SOURCE_DOI = "general.source.doi" | |
SOURCE_UUID = "general.source.uuid" | |
SOURCE_REPO_URL = "general.source.repo_url" # Model Source Repository (git/svn/etc...) | |
# Base Model Source. There can be more than one source if it's a merged | |
# model like with 'Mistral-7B-Merge-14-v0.1'. This will assist in | |
# tracing linage of models as it is finetuned or merged over time. | |
BASE_MODEL_COUNT = "general.base_model.count" | |
BASE_MODEL_NAME = "general.base_model.{id}.name" | |
BASE_MODEL_AUTHOR = "general.base_model.{id}.author" | |
BASE_MODEL_VERSION = "general.base_model.{id}.version" | |
BASE_MODEL_ORGANIZATION = "general.base_model.{id}.organization" | |
BASE_MODEL_URL = "general.base_model.{id}.url" # Model Website/Paper | |
BASE_MODEL_DOI = "general.base_model.{id}.doi" | |
BASE_MODEL_UUID = "general.base_model.{id}.uuid" | |
BASE_MODEL_REPO_URL = "general.base_model.{id}.repo_url" # Model Source Repository (git/svn/etc...) | |
# Array based KV stores | |
TAGS = "general.tags" | |
LANGUAGES = "general.languages" | |
DATASETS = "general.datasets" | |
class LLM: | |
VOCAB_SIZE = "{arch}.vocab_size" | |
CONTEXT_LENGTH = "{arch}.context_length" | |
EMBEDDING_LENGTH = "{arch}.embedding_length" | |
BLOCK_COUNT = "{arch}.block_count" | |
LEADING_DENSE_BLOCK_COUNT = "{arch}.leading_dense_block_count" | |
FEED_FORWARD_LENGTH = "{arch}.feed_forward_length" | |
EXPERT_FEED_FORWARD_LENGTH = "{arch}.expert_feed_forward_length" | |
EXPERT_SHARED_FEED_FORWARD_LENGTH = "{arch}.expert_shared_feed_forward_length" | |
USE_PARALLEL_RESIDUAL = "{arch}.use_parallel_residual" | |
TENSOR_DATA_LAYOUT = "{arch}.tensor_data_layout" | |
EXPERT_COUNT = "{arch}.expert_count" | |
EXPERT_USED_COUNT = "{arch}.expert_used_count" | |
EXPERT_SHARED_COUNT = "{arch}.expert_shared_count" | |
EXPERT_WEIGHTS_SCALE = "{arch}.expert_weights_scale" | |
POOLING_TYPE = "{arch}.pooling_type" | |
LOGIT_SCALE = "{arch}.logit_scale" | |
DECODER_START_TOKEN_ID = "{arch}.decoder_start_token_id" | |
ATTN_LOGIT_SOFTCAPPING = "{arch}.attn_logit_softcapping" | |
FINAL_LOGIT_SOFTCAPPING = "{arch}.final_logit_softcapping" | |
SWIN_NORM = "{arch}.swin_norm" | |
RESCALE_EVERY_N_LAYERS = "{arch}.rescale_every_n_layers" | |
TIME_MIX_EXTRA_DIM = "{arch}.time_mix_extra_dim" | |
TIME_DECAY_EXTRA_DIM = "{arch}.time_decay_extra_dim" | |
RESIDUAL_SCALE = "{arch}.residual_scale" | |
EMBEDDING_SCALE = "{arch}.embedding_scale" | |
class Attention: | |
HEAD_COUNT = "{arch}.attention.head_count" | |
HEAD_COUNT_KV = "{arch}.attention.head_count_kv" | |
MAX_ALIBI_BIAS = "{arch}.attention.max_alibi_bias" | |
CLAMP_KQV = "{arch}.attention.clamp_kqv" | |
KEY_LENGTH = "{arch}.attention.key_length" | |
VALUE_LENGTH = "{arch}.attention.value_length" | |
LAYERNORM_EPS = "{arch}.attention.layer_norm_epsilon" | |
LAYERNORM_RMS_EPS = "{arch}.attention.layer_norm_rms_epsilon" | |
CAUSAL = "{arch}.attention.causal" | |
Q_LORA_RANK = "{arch}.attention.q_lora_rank" | |
KV_LORA_RANK = "{arch}.attention.kv_lora_rank" | |
REL_BUCKETS_COUNT = "{arch}.attention.relative_buckets_count" | |
SLIDING_WINDOW = "{arch}.attention.sliding_window" | |
SCALE = "{arch}.attention.scale" | |
class Rope: | |
DIMENSION_COUNT = "{arch}.rope.dimension_count" | |
FREQ_BASE = "{arch}.rope.freq_base" | |
SCALING_TYPE = "{arch}.rope.scaling.type" | |
SCALING_FACTOR = "{arch}.rope.scaling.factor" | |
SCALING_ATTN_FACTOR = "{arch}.rope.scaling.attn_factor" | |
SCALING_ORIG_CTX_LEN = "{arch}.rope.scaling.original_context_length" | |
SCALING_FINETUNED = "{arch}.rope.scaling.finetuned" | |
SCALING_YARN_LOG_MUL = "{arch}.rope.scaling.yarn_log_multiplier" | |
class Split: | |
LLM_KV_SPLIT_NO = "split.no" | |
LLM_KV_SPLIT_COUNT = "split.count" | |
LLM_KV_SPLIT_TENSORS_COUNT = "split.tensors.count" | |
class SSM: | |
CONV_KERNEL = "{arch}.ssm.conv_kernel" | |
INNER_SIZE = "{arch}.ssm.inner_size" | |
STATE_SIZE = "{arch}.ssm.state_size" | |
TIME_STEP_RANK = "{arch}.ssm.time_step_rank" | |
DT_B_C_RMS = "{arch}.ssm.dt_b_c_rms" | |
class WKV: | |
HEAD_SIZE = "{arch}.wkv.head_size" | |
class Tokenizer: | |
MODEL = "tokenizer.ggml.model" | |
PRE = "tokenizer.ggml.pre" | |
LIST = "tokenizer.ggml.tokens" | |
TOKEN_TYPE = "tokenizer.ggml.token_type" | |
TOKEN_TYPE_COUNT = "tokenizer.ggml.token_type_count" # for BERT-style token types | |
SCORES = "tokenizer.ggml.scores" | |
MERGES = "tokenizer.ggml.merges" | |
BOS_ID = "tokenizer.ggml.bos_token_id" | |
EOS_ID = "tokenizer.ggml.eos_token_id" | |
EOT_ID = "tokenizer.ggml.eot_token_id" | |
EOM_ID = "tokenizer.ggml.eom_token_id" | |
UNK_ID = "tokenizer.ggml.unknown_token_id" | |
SEP_ID = "tokenizer.ggml.seperator_token_id" | |
PAD_ID = "tokenizer.ggml.padding_token_id" | |
CLS_ID = "tokenizer.ggml.cls_token_id" | |
MASK_ID = "tokenizer.ggml.mask_token_id" | |
ADD_BOS = "tokenizer.ggml.add_bos_token" | |
ADD_EOS = "tokenizer.ggml.add_eos_token" | |
ADD_PREFIX = "tokenizer.ggml.add_space_prefix" | |
REMOVE_EXTRA_WS = "tokenizer.ggml.remove_extra_whitespaces" | |
PRECOMPILED_CHARSMAP = "tokenizer.ggml.precompiled_charsmap" | |
HF_JSON = "tokenizer.huggingface.json" | |
RWKV = "tokenizer.rwkv.world" | |
CHAT_TEMPLATE = "tokenizer.chat_template" | |
CHAT_TEMPLATE_N = "tokenizer.chat_template.{name}" | |
CHAT_TEMPLATES = "tokenizer.chat_templates" | |
# FIM/Infill special tokens constants | |
FIM_PRE_ID = "tokenizer.ggml.fim_pre_token_id" | |
FIM_SUF_ID = "tokenizer.ggml.fim_suf_token_id" | |
FIM_MID_ID = "tokenizer.ggml.fim_mid_token_id" | |
FIM_PAD_ID = "tokenizer.ggml.fim_pad_token_id" | |
FIM_REP_ID = "tokenizer.ggml.fim_rep_token_id" | |
FIM_SEP_ID = "tokenizer.ggml.fim_sep_token_id" | |
# deprecated: | |
PREFIX_ID = "tokenizer.ggml.prefix_token_id" | |
SUFFIX_ID = "tokenizer.ggml.suffix_token_id" | |
MIDDLE_ID = "tokenizer.ggml.middle_token_id" | |
class Adapter: | |
TYPE = "adapter.type" | |
LORA_ALPHA = "adapter.lora.alpha" | |
# | |
# recommended mapping of model tensor names for storage in gguf | |
# | |
class GGUFType: | |
MODEL = "model" | |
ADAPTER = "adapter" | |
class MODEL_ARCH(IntEnum): | |
LLAMA = auto() | |
FALCON = auto() | |
BAICHUAN = auto() | |
GROK = auto() | |
GPT2 = auto() | |
GPTJ = auto() | |
GPTNEOX = auto() | |
MPT = auto() | |
STARCODER = auto() | |
REFACT = auto() | |
BERT = auto() | |
NOMIC_BERT = auto() | |
JINA_BERT_V2 = auto() | |
BLOOM = auto() | |
STABLELM = auto() | |
QWEN = auto() | |
QWEN2 = auto() | |
QWEN2MOE = auto() | |
PHI2 = auto() | |
PHI3 = auto() | |
PLAMO = auto() | |
CODESHELL = auto() | |
ORION = auto() | |
INTERNLM2 = auto() | |
MINICPM = auto() | |
MINICPM3 = auto() | |
GEMMA = auto() | |
GEMMA2 = auto() | |
STARCODER2 = auto() | |
RWKV6 = auto() | |
MAMBA = auto() | |
XVERSE = auto() | |
COMMAND_R = auto() | |
DBRX = auto() | |
OLMO = auto() | |
OLMOE = auto() | |
OPENELM = auto() | |
ARCTIC = auto() | |
DEEPSEEK2 = auto() | |
CHATGLM = auto() | |
BITNET = auto() | |
T5 = auto() | |
T5ENCODER = auto() | |
JAIS = auto() | |
NEMOTRON = auto() | |
EXAONE = auto() | |
GRANITE = auto() | |
GRANITE_MOE = auto() | |
CHAMELEON = auto() | |
class MODEL_TENSOR(IntEnum): | |
TOKEN_EMBD = auto() | |
TOKEN_EMBD_NORM = auto() | |
TOKEN_TYPES = auto() | |
POS_EMBD = auto() | |
OUTPUT = auto() | |
OUTPUT_NORM = auto() | |
ROPE_FREQS = auto() | |
ROPE_FACTORS_LONG = auto() | |
ROPE_FACTORS_SHORT = auto() | |
ATTN_Q = auto() | |
ATTN_K = auto() | |
ATTN_V = auto() | |
ATTN_QKV = auto() | |
ATTN_OUT = auto() | |
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() | |
FFN_ACT = auto() | |
FFN_NORM_EXP = auto() | |
FFN_GATE_EXP = auto() | |
FFN_DOWN_EXP = auto() | |
FFN_UP_EXP = auto() | |
FFN_GATE_SHEXP = auto() | |
FFN_DOWN_SHEXP = auto() | |
FFN_UP_SHEXP = auto() | |
ATTN_Q_NORM = auto() | |
ATTN_K_NORM = auto() | |
LAYER_OUT_NORM = auto() | |
SSM_IN = auto() | |
SSM_CONV1D = auto() | |
SSM_X = auto() | |
SSM_DT = auto() | |
SSM_A = auto() | |
SSM_D = auto() | |
SSM_OUT = auto() | |
TIME_MIX_W1 = auto() | |
TIME_MIX_W2 = auto() | |
TIME_MIX_LERP_X = auto() | |
TIME_MIX_LERP_K = auto() | |
TIME_MIX_LERP_V = auto() | |
TIME_MIX_LERP_R = auto() | |
TIME_MIX_LERP_G = auto() | |
TIME_MIX_LERP_W = auto() | |
TIME_MIX_FIRST = auto() | |
TIME_MIX_DECAY = auto() | |
TIME_MIX_DECAY_W1 = auto() | |
TIME_MIX_DECAY_W2 = auto() | |
TIME_MIX_KEY = auto() | |
TIME_MIX_VALUE = auto() | |
TIME_MIX_RECEPTANCE = auto() | |
TIME_MIX_GATE = auto() | |
TIME_MIX_LN = auto() | |
TIME_MIX_OUTPUT = auto() | |
CHANNEL_MIX_LERP_K = auto() | |
CHANNEL_MIX_LERP_R = auto() | |
CHANNEL_MIX_KEY = auto() | |
CHANNEL_MIX_RECEPTANCE = auto() | |
CHANNEL_MIX_VALUE = auto() | |
ATTN_Q_A = auto() | |
ATTN_Q_B = auto() | |
ATTN_KV_A_MQA = auto() | |
ATTN_KV_B = auto() | |
ATTN_Q_A_NORM = auto() | |
ATTN_KV_A_NORM = auto() | |
FFN_SUB_NORM = auto() | |
ATTN_SUB_NORM = auto() | |
DEC_ATTN_NORM = auto() | |
DEC_ATTN_Q = auto() | |
DEC_ATTN_K = auto() | |
DEC_ATTN_V = auto() | |
DEC_ATTN_OUT = auto() | |
DEC_ATTN_REL_B = auto() | |
DEC_CROSS_ATTN_NORM = auto() | |
DEC_CROSS_ATTN_Q = auto() | |
DEC_CROSS_ATTN_K = auto() | |
DEC_CROSS_ATTN_V = auto() | |
DEC_CROSS_ATTN_OUT = auto() | |
DEC_CROSS_ATTN_REL_B = auto() | |
DEC_FFN_NORM = auto() | |
DEC_FFN_GATE = auto() | |
DEC_FFN_DOWN = auto() | |
DEC_FFN_UP = auto() | |
DEC_OUTPUT_NORM = auto() | |
ENC_ATTN_NORM = auto() | |
ENC_ATTN_Q = auto() | |
ENC_ATTN_K = auto() | |
ENC_ATTN_V = auto() | |
ENC_ATTN_OUT = auto() | |
ENC_ATTN_REL_B = auto() | |
ENC_FFN_NORM = auto() | |
ENC_FFN_GATE = auto() | |
ENC_FFN_DOWN = auto() | |
ENC_FFN_UP = auto() | |
ENC_OUTPUT_NORM = auto() | |
CLS = auto() # classifier | |
CLS_OUT = auto() # classifier output projection | |
MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = { | |
MODEL_ARCH.LLAMA: "llama", | |
MODEL_ARCH.FALCON: "falcon", | |
MODEL_ARCH.BAICHUAN: "baichuan", | |
MODEL_ARCH.GROK: "grok", | |
MODEL_ARCH.GPT2: "gpt2", | |
MODEL_ARCH.GPTJ: "gptj", | |
MODEL_ARCH.GPTNEOX: "gptneox", | |
MODEL_ARCH.MPT: "mpt", | |
MODEL_ARCH.STARCODER: "starcoder", | |
MODEL_ARCH.REFACT: "refact", | |
MODEL_ARCH.BERT: "bert", | |
MODEL_ARCH.NOMIC_BERT: "nomic-bert", | |
MODEL_ARCH.JINA_BERT_V2: "jina-bert-v2", | |
MODEL_ARCH.BLOOM: "bloom", | |
MODEL_ARCH.STABLELM: "stablelm", | |
MODEL_ARCH.QWEN: "qwen", | |
MODEL_ARCH.QWEN2: "qwen2", | |
MODEL_ARCH.QWEN2MOE: "qwen2moe", | |
MODEL_ARCH.PHI2: "phi2", | |
MODEL_ARCH.PHI3: "phi3", | |
MODEL_ARCH.PLAMO: "plamo", | |
MODEL_ARCH.CODESHELL: "codeshell", | |
MODEL_ARCH.ORION: "orion", | |
MODEL_ARCH.INTERNLM2: "internlm2", | |
MODEL_ARCH.MINICPM: "minicpm", | |
MODEL_ARCH.MINICPM3: "minicpm3", | |
MODEL_ARCH.GEMMA: "gemma", | |
MODEL_ARCH.GEMMA2: "gemma2", | |
MODEL_ARCH.STARCODER2: "starcoder2", | |
MODEL_ARCH.RWKV6: "rwkv6", | |
MODEL_ARCH.MAMBA: "mamba", | |
MODEL_ARCH.XVERSE: "xverse", | |
MODEL_ARCH.COMMAND_R: "command-r", | |
MODEL_ARCH.DBRX: "dbrx", | |
MODEL_ARCH.OLMO: "olmo", | |
MODEL_ARCH.OLMOE: "olmoe", | |
MODEL_ARCH.OPENELM: "openelm", | |
MODEL_ARCH.ARCTIC: "arctic", | |
MODEL_ARCH.DEEPSEEK2: "deepseek2", | |
MODEL_ARCH.CHATGLM: "chatglm", | |
MODEL_ARCH.BITNET: "bitnet", | |
MODEL_ARCH.T5: "t5", | |
MODEL_ARCH.T5ENCODER: "t5encoder", | |
MODEL_ARCH.JAIS: "jais", | |
MODEL_ARCH.NEMOTRON: "nemotron", | |
MODEL_ARCH.EXAONE: "exaone", | |
MODEL_ARCH.GRANITE: "granite", | |
MODEL_ARCH.GRANITE_MOE: "granitemoe", | |
MODEL_ARCH.CHAMELEON: "chameleon", | |
} | |
TENSOR_NAMES: dict[MODEL_TENSOR, str] = { | |
MODEL_TENSOR.TOKEN_EMBD: "token_embd", | |
MODEL_TENSOR.TOKEN_EMBD_NORM: "token_embd_norm", | |
MODEL_TENSOR.TOKEN_TYPES: "token_types", | |
MODEL_TENSOR.POS_EMBD: "position_embd", | |
MODEL_TENSOR.OUTPUT_NORM: "output_norm", | |
MODEL_TENSOR.OUTPUT: "output", | |
MODEL_TENSOR.ROPE_FREQS: "rope_freqs", | |
MODEL_TENSOR.ROPE_FACTORS_LONG: "rope_factors_long", | |
MODEL_TENSOR.ROPE_FACTORS_SHORT: "rope_factors_short", | |
MODEL_TENSOR.ATTN_NORM: "blk.{bid}.attn_norm", | |
MODEL_TENSOR.ATTN_NORM_2: "blk.{bid}.attn_norm_2", | |
MODEL_TENSOR.ATTN_QKV: "blk.{bid}.attn_qkv", | |
MODEL_TENSOR.ATTN_Q: "blk.{bid}.attn_q", | |
MODEL_TENSOR.ATTN_K: "blk.{bid}.attn_k", | |
MODEL_TENSOR.ATTN_V: "blk.{bid}.attn_v", | |
MODEL_TENSOR.ATTN_OUT: "blk.{bid}.attn_output", | |
MODEL_TENSOR.ATTN_ROT_EMBD: "blk.{bid}.attn_rot_embd", | |
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", | |
MODEL_TENSOR.FFN_GATE_SHEXP: "blk.{bid}.ffn_gate_shexp", | |
MODEL_TENSOR.FFN_DOWN_SHEXP: "blk.{bid}.ffn_down_shexp", | |
MODEL_TENSOR.FFN_UP_SHEXP: "blk.{bid}.ffn_up_shexp", | |
MODEL_TENSOR.FFN_ACT: "blk.{bid}.ffn", | |
MODEL_TENSOR.FFN_NORM_EXP: "blk.{bid}.ffn_norm_exps", | |
MODEL_TENSOR.FFN_GATE_EXP: "blk.{bid}.ffn_gate_exps", | |
MODEL_TENSOR.FFN_DOWN_EXP: "blk.{bid}.ffn_down_exps", | |
MODEL_TENSOR.FFN_UP_EXP: "blk.{bid}.ffn_up_exps", | |
MODEL_TENSOR.LAYER_OUT_NORM: "blk.{bid}.layer_output_norm", | |
MODEL_TENSOR.SSM_IN: "blk.{bid}.ssm_in", | |
MODEL_TENSOR.SSM_CONV1D: "blk.{bid}.ssm_conv1d", | |
MODEL_TENSOR.SSM_X: "blk.{bid}.ssm_x", | |
MODEL_TENSOR.SSM_DT: "blk.{bid}.ssm_dt", | |
MODEL_TENSOR.SSM_A: "blk.{bid}.ssm_a", | |
MODEL_TENSOR.SSM_D: "blk.{bid}.ssm_d", | |
MODEL_TENSOR.SSM_OUT: "blk.{bid}.ssm_out", | |
MODEL_TENSOR.TIME_MIX_W1: "blk.{bid}.time_mix_w1", | |
MODEL_TENSOR.TIME_MIX_W2: "blk.{bid}.time_mix_w2", | |
MODEL_TENSOR.TIME_MIX_LERP_X: "blk.{bid}.time_mix_lerp_x", | |
MODEL_TENSOR.TIME_MIX_LERP_K: "blk.{bid}.time_mix_lerp_k", | |
MODEL_TENSOR.TIME_MIX_LERP_V: "blk.{bid}.time_mix_lerp_v", | |
MODEL_TENSOR.TIME_MIX_LERP_R: "blk.{bid}.time_mix_lerp_r", | |
MODEL_TENSOR.TIME_MIX_LERP_G: "blk.{bid}.time_mix_lerp_g", | |
MODEL_TENSOR.TIME_MIX_LERP_W: "blk.{bid}.time_mix_lerp_w", | |
MODEL_TENSOR.TIME_MIX_FIRST: "blk.{bid}.time_mix_first", | |
MODEL_TENSOR.TIME_MIX_DECAY: "blk.{bid}.time_mix_decay", | |
MODEL_TENSOR.TIME_MIX_DECAY_W1: "blk.{bid}.time_mix_decay_w1", | |
MODEL_TENSOR.TIME_MIX_DECAY_W2: "blk.{bid}.time_mix_decay_w2", | |
MODEL_TENSOR.TIME_MIX_KEY: "blk.{bid}.time_mix_key", | |
MODEL_TENSOR.TIME_MIX_VALUE: "blk.{bid}.time_mix_value", | |
MODEL_TENSOR.TIME_MIX_RECEPTANCE: "blk.{bid}.time_mix_receptance", | |
MODEL_TENSOR.TIME_MIX_GATE: "blk.{bid}.time_mix_gate", | |
MODEL_TENSOR.TIME_MIX_LN: "blk.{bid}.time_mix_ln", | |
MODEL_TENSOR.TIME_MIX_OUTPUT: "blk.{bid}.time_mix_output", | |
MODEL_TENSOR.CHANNEL_MIX_LERP_K: "blk.{bid}.channel_mix_lerp_k", | |
MODEL_TENSOR.CHANNEL_MIX_LERP_R: "blk.{bid}.channel_mix_lerp_r", | |
MODEL_TENSOR.CHANNEL_MIX_KEY: "blk.{bid}.channel_mix_key", | |
MODEL_TENSOR.CHANNEL_MIX_RECEPTANCE: "blk.{bid}.channel_mix_receptance", | |
MODEL_TENSOR.CHANNEL_MIX_VALUE: "blk.{bid}.channel_mix_value", | |
MODEL_TENSOR.ATTN_Q_A: "blk.{bid}.attn_q_a", | |
MODEL_TENSOR.ATTN_Q_B: "blk.{bid}.attn_q_b", | |
MODEL_TENSOR.ATTN_KV_A_MQA: "blk.{bid}.attn_kv_a_mqa", | |
MODEL_TENSOR.ATTN_KV_B: "blk.{bid}.attn_kv_b", | |
MODEL_TENSOR.ATTN_Q_A_NORM: "blk.{bid}.attn_q_a_norm", | |
MODEL_TENSOR.ATTN_KV_A_NORM: "blk.{bid}.attn_kv_a_norm", | |
MODEL_TENSOR.ATTN_SUB_NORM: "blk.{bid}.attn_sub_norm", | |
MODEL_TENSOR.FFN_SUB_NORM: "blk.{bid}.ffn_sub_norm", | |
MODEL_TENSOR.DEC_ATTN_NORM: "dec.blk.{bid}.attn_norm", | |
MODEL_TENSOR.DEC_ATTN_Q: "dec.blk.{bid}.attn_q", | |
MODEL_TENSOR.DEC_ATTN_K: "dec.blk.{bid}.attn_k", | |
MODEL_TENSOR.DEC_ATTN_V: "dec.blk.{bid}.attn_v", | |
MODEL_TENSOR.DEC_ATTN_OUT: "dec.blk.{bid}.attn_o", | |
MODEL_TENSOR.DEC_ATTN_REL_B: "dec.blk.{bid}.attn_rel_b", | |
MODEL_TENSOR.DEC_CROSS_ATTN_NORM: "dec.blk.{bid}.cross_attn_norm", | |
MODEL_TENSOR.DEC_CROSS_ATTN_Q: "dec.blk.{bid}.cross_attn_q", | |
MODEL_TENSOR.DEC_CROSS_ATTN_K: "dec.blk.{bid}.cross_attn_k", | |
MODEL_TENSOR.DEC_CROSS_ATTN_V: "dec.blk.{bid}.cross_attn_v", | |
MODEL_TENSOR.DEC_CROSS_ATTN_OUT: "dec.blk.{bid}.cross_attn_o", | |
MODEL_TENSOR.DEC_CROSS_ATTN_REL_B: "dec.blk.{bid}.cross_attn_rel_b", | |
MODEL_TENSOR.DEC_FFN_NORM: "dec.blk.{bid}.ffn_norm", | |
MODEL_TENSOR.DEC_FFN_GATE: "dec.blk.{bid}.ffn_gate", | |
MODEL_TENSOR.DEC_FFN_DOWN: "dec.blk.{bid}.ffn_down", | |
MODEL_TENSOR.DEC_FFN_UP: "dec.blk.{bid}.ffn_up", | |
MODEL_TENSOR.DEC_OUTPUT_NORM: "dec.output_norm", | |
MODEL_TENSOR.ENC_ATTN_NORM: "enc.blk.{bid}.attn_norm", | |
MODEL_TENSOR.ENC_ATTN_Q: "enc.blk.{bid}.attn_q", | |
MODEL_TENSOR.ENC_ATTN_K: "enc.blk.{bid}.attn_k", | |
MODEL_TENSOR.ENC_ATTN_V: "enc.blk.{bid}.attn_v", | |
MODEL_TENSOR.ENC_ATTN_OUT: "enc.blk.{bid}.attn_o", | |
MODEL_TENSOR.ENC_ATTN_REL_B: "enc.blk.{bid}.attn_rel_b", | |
MODEL_TENSOR.ENC_FFN_NORM: "enc.blk.{bid}.ffn_norm", | |
MODEL_TENSOR.ENC_FFN_GATE: "enc.blk.{bid}.ffn_gate", | |
MODEL_TENSOR.ENC_FFN_DOWN: "enc.blk.{bid}.ffn_down", | |
MODEL_TENSOR.ENC_FFN_UP: "enc.blk.{bid}.ffn_up", | |
MODEL_TENSOR.ENC_OUTPUT_NORM: "enc.output_norm", | |
MODEL_TENSOR.CLS: "cls", | |
MODEL_TENSOR.CLS_OUT: "cls.output", | |
} | |
MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { | |
MODEL_ARCH.LLAMA: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
], | |
MODEL_ARCH.GROK: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.ATTN_OUT_NORM, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
MODEL_TENSOR.LAYER_OUT_NORM, | |
], | |
MODEL_ARCH.GPTNEOX: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.FALCON: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_NORM_2, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.BAICHUAN: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.STARCODER: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.POS_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.BERT: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.TOKEN_EMBD_NORM, | |
MODEL_TENSOR.TOKEN_TYPES, | |
MODEL_TENSOR.POS_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_OUT_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.LAYER_OUT_NORM, | |
MODEL_TENSOR.CLS, | |
MODEL_TENSOR.CLS_OUT, | |
], | |
MODEL_ARCH.NOMIC_BERT: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.TOKEN_EMBD_NORM, | |
MODEL_TENSOR.TOKEN_TYPES, | |
MODEL_TENSOR.POS_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_OUT_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.LAYER_OUT_NORM, | |
], | |
MODEL_ARCH.JINA_BERT_V2: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.TOKEN_EMBD_NORM, | |
MODEL_TENSOR.TOKEN_TYPES, | |
MODEL_TENSOR.ATTN_NORM_2, | |
MODEL_TENSOR.ATTN_OUT_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_K_NORM, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.LAYER_OUT_NORM, | |
MODEL_TENSOR.CLS, | |
], | |
MODEL_ARCH.MPT: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_ACT, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K_NORM, | |
MODEL_TENSOR.POS_EMBD, | |
], | |
MODEL_ARCH.GPTJ: [ | |
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_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.BLOOM: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.TOKEN_EMBD_NORM, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.STABLELM: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
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_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K_NORM, | |
], | |
MODEL_ARCH.QWEN: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.QWEN2: [ | |
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.QWEN2MOE: [ | |
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_INP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
MODEL_TENSOR.FFN_GATE_INP_SHEXP, | |
MODEL_TENSOR.FFN_GATE_SHEXP, | |
MODEL_TENSOR.FFN_DOWN_SHEXP, | |
MODEL_TENSOR.FFN_UP_SHEXP, | |
], | |
MODEL_ARCH.PLAMO: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.GPT2: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.POS_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.PHI2: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.PHI3: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FACTORS_LONG, | |
MODEL_TENSOR.ROPE_FACTORS_SHORT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.CODESHELL: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.POS_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.ORION: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.INTERNLM2: [ | |
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.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.MINICPM: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
], | |
MODEL_ARCH.MINICPM3: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FACTORS_LONG, | |
MODEL_TENSOR.ROPE_FACTORS_SHORT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q_A, | |
MODEL_TENSOR.ATTN_Q_B, | |
MODEL_TENSOR.ATTN_KV_A_MQA, | |
MODEL_TENSOR.ATTN_KV_B, | |
MODEL_TENSOR.ATTN_Q_A_NORM, | |
MODEL_TENSOR.ATTN_KV_A_NORM, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.GEMMA: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_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.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, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.RWKV6: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.TOKEN_EMBD_NORM, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_NORM_2, | |
MODEL_TENSOR.TIME_MIX_W1, | |
MODEL_TENSOR.TIME_MIX_W2, | |
MODEL_TENSOR.TIME_MIX_LERP_X, | |
MODEL_TENSOR.TIME_MIX_LERP_K, | |
MODEL_TENSOR.TIME_MIX_LERP_V, | |
MODEL_TENSOR.TIME_MIX_LERP_R, | |
MODEL_TENSOR.TIME_MIX_LERP_G, | |
MODEL_TENSOR.TIME_MIX_LERP_W, | |
MODEL_TENSOR.TIME_MIX_FIRST, | |
MODEL_TENSOR.TIME_MIX_DECAY, | |
MODEL_TENSOR.TIME_MIX_DECAY_W1, | |
MODEL_TENSOR.TIME_MIX_DECAY_W2, | |
MODEL_TENSOR.TIME_MIX_KEY, | |
MODEL_TENSOR.TIME_MIX_VALUE, | |
MODEL_TENSOR.TIME_MIX_RECEPTANCE, | |
MODEL_TENSOR.TIME_MIX_GATE, | |
MODEL_TENSOR.TIME_MIX_LN, | |
MODEL_TENSOR.TIME_MIX_OUTPUT, | |
MODEL_TENSOR.CHANNEL_MIX_LERP_K, | |
MODEL_TENSOR.CHANNEL_MIX_LERP_R, | |
MODEL_TENSOR.CHANNEL_MIX_KEY, | |
MODEL_TENSOR.CHANNEL_MIX_RECEPTANCE, | |
MODEL_TENSOR.CHANNEL_MIX_VALUE, | |
], | |
MODEL_ARCH.MAMBA: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.SSM_IN, | |
MODEL_TENSOR.SSM_CONV1D, | |
MODEL_TENSOR.SSM_X, | |
MODEL_TENSOR.SSM_DT, | |
MODEL_TENSOR.SSM_A, | |
MODEL_TENSOR.SSM_D, | |
MODEL_TENSOR.SSM_OUT, | |
], | |
MODEL_ARCH.XVERSE: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.COMMAND_R: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_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_K_NORM, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
], | |
MODEL_ARCH.DBRX: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_OUT_NORM, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
], | |
MODEL_ARCH.OLMO: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT, | |
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_ARCH.OLMOE: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K_NORM, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
], | |
MODEL_ARCH.OPENELM: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K_NORM, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.ARCTIC: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_NORM_EXP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
], | |
MODEL_ARCH.DEEPSEEK2: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_Q_A, | |
MODEL_TENSOR.ATTN_Q_B, | |
MODEL_TENSOR.ATTN_KV_A_MQA, | |
MODEL_TENSOR.ATTN_KV_B, | |
MODEL_TENSOR.ATTN_Q_A_NORM, | |
MODEL_TENSOR.ATTN_KV_A_NORM, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_GATE_INP, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
MODEL_TENSOR.FFN_GATE_SHEXP, | |
MODEL_TENSOR.FFN_DOWN_SHEXP, | |
MODEL_TENSOR.FFN_UP_SHEXP, | |
], | |
MODEL_ARCH.CHATGLM : [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.BITNET: [ | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
MODEL_TENSOR.ATTN_SUB_NORM, | |
MODEL_TENSOR.FFN_SUB_NORM, | |
], | |
MODEL_ARCH.T5: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.DEC_ATTN_NORM, | |
MODEL_TENSOR.DEC_ATTN_Q, | |
MODEL_TENSOR.DEC_ATTN_K, | |
MODEL_TENSOR.DEC_ATTN_V, | |
MODEL_TENSOR.DEC_ATTN_OUT, | |
MODEL_TENSOR.DEC_ATTN_REL_B, | |
MODEL_TENSOR.DEC_CROSS_ATTN_NORM, | |
MODEL_TENSOR.DEC_CROSS_ATTN_Q, | |
MODEL_TENSOR.DEC_CROSS_ATTN_K, | |
MODEL_TENSOR.DEC_CROSS_ATTN_V, | |
MODEL_TENSOR.DEC_CROSS_ATTN_OUT, | |
MODEL_TENSOR.DEC_CROSS_ATTN_REL_B, | |
MODEL_TENSOR.DEC_FFN_NORM, | |
MODEL_TENSOR.DEC_FFN_GATE, | |
MODEL_TENSOR.DEC_FFN_DOWN, | |
MODEL_TENSOR.DEC_FFN_UP, | |
MODEL_TENSOR.DEC_OUTPUT_NORM, | |
MODEL_TENSOR.ENC_ATTN_NORM, | |
MODEL_TENSOR.ENC_ATTN_Q, | |
MODEL_TENSOR.ENC_ATTN_K, | |
MODEL_TENSOR.ENC_ATTN_V, | |
MODEL_TENSOR.ENC_ATTN_OUT, | |
MODEL_TENSOR.ENC_ATTN_REL_B, | |
MODEL_TENSOR.ENC_FFN_NORM, | |
MODEL_TENSOR.ENC_FFN_GATE, | |
MODEL_TENSOR.ENC_FFN_DOWN, | |
MODEL_TENSOR.ENC_FFN_UP, | |
MODEL_TENSOR.ENC_OUTPUT_NORM, | |
], | |
MODEL_ARCH.T5ENCODER: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ENC_ATTN_NORM, | |
MODEL_TENSOR.ENC_ATTN_Q, | |
MODEL_TENSOR.ENC_ATTN_K, | |
MODEL_TENSOR.ENC_ATTN_V, | |
MODEL_TENSOR.ENC_ATTN_OUT, | |
MODEL_TENSOR.ENC_ATTN_REL_B, | |
MODEL_TENSOR.ENC_FFN_NORM, | |
MODEL_TENSOR.ENC_FFN_GATE, | |
MODEL_TENSOR.ENC_FFN_DOWN, | |
MODEL_TENSOR.ENC_FFN_UP, | |
MODEL_TENSOR.ENC_OUTPUT_NORM, | |
], | |
MODEL_ARCH.JAIS: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_QKV, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.NEMOTRON: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.EXAONE: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
MODEL_ARCH.GRANITE: [ | |
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.GRANITE_MOE: [ | |
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_INP, | |
MODEL_TENSOR.FFN_GATE_EXP, | |
MODEL_TENSOR.FFN_DOWN_EXP, | |
MODEL_TENSOR.FFN_UP_EXP, | |
], | |
MODEL_ARCH.CHAMELEON: [ | |
MODEL_TENSOR.TOKEN_EMBD, | |
MODEL_TENSOR.OUTPUT_NORM, | |
MODEL_TENSOR.OUTPUT, | |
MODEL_TENSOR.ATTN_NORM, | |
MODEL_TENSOR.ATTN_Q, | |
MODEL_TENSOR.ATTN_Q_NORM, | |
MODEL_TENSOR.ATTN_K, | |
MODEL_TENSOR.ATTN_K_NORM, | |
MODEL_TENSOR.ATTN_V, | |
MODEL_TENSOR.ATTN_OUT, | |
MODEL_TENSOR.FFN_NORM, | |
MODEL_TENSOR.FFN_GATE, | |
MODEL_TENSOR.FFN_DOWN, | |
MODEL_TENSOR.FFN_UP, | |
], | |
# TODO | |
} | |
# tensors that will not be serialized | |
MODEL_TENSOR_SKIP: dict[MODEL_ARCH, list[MODEL_TENSOR]] = { | |
MODEL_ARCH.LLAMA: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.BAICHUAN: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.QWEN: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.CODESHELL: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.ORION: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.STARCODER2: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.XVERSE: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.DEEPSEEK2: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
MODEL_ARCH.CHATGLM: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
], | |
MODEL_ARCH.NEMOTRON: [ | |
MODEL_TENSOR.ROPE_FREQS, | |
MODEL_TENSOR.ATTN_ROT_EMBD, | |
], | |
} | |
# | |
# types | |
# | |
class TokenType(IntEnum): | |
NORMAL = 1 | |
UNKNOWN = 2 | |
CONTROL = 3 | |
USER_DEFINED = 4 | |
UNUSED = 5 | |
BYTE = 6 | |
class RopeScalingType(Enum): | |
NONE = 'none' | |
LINEAR = 'linear' | |
YARN = 'yarn' | |
class PoolingType(IntEnum): | |
NONE = 0 | |
MEAN = 1 | |
CLS = 2 | |
class GGMLQuantizationType(IntEnum): | |
F32 = 0 | |
F16 = 1 | |
Q4_0 = 2 | |
Q4_1 = 3 | |
Q5_0 = 6 | |
Q5_1 = 7 | |
Q8_0 = 8 | |
Q8_1 = 9 | |
Q2_K = 10 | |
Q3_K = 11 | |
Q4_K = 12 | |
Q5_K = 13 | |
Q6_K = 14 | |
Q8_K = 15 | |
IQ2_XXS = 16 | |
IQ2_XS = 17 | |
IQ3_XXS = 18 | |
IQ1_S = 19 | |
IQ4_NL = 20 | |
IQ3_S = 21 | |
IQ2_S = 22 | |
IQ4_XS = 23 | |
I8 = 24 | |
I16 = 25 | |
I32 = 26 | |
I64 = 27 | |
F64 = 28 | |
IQ1_M = 29 | |
BF16 = 30 | |
Q4_0_4_4 = 31 | |
Q4_0_4_8 = 32 | |
Q4_0_8_8 = 33 | |
TQ1_0 = 34 | |
TQ2_0 = 35 | |
# TODO: add GGMLFileType from ggml_ftype in ggml.h | |
# from llama_ftype in llama.h | |
# ALL VALUES SHOULD BE THE SAME HERE AS THEY ARE OVER THERE. | |
class LlamaFileType(IntEnum): | |
ALL_F32 = 0 | |
MOSTLY_F16 = 1 # except 1d tensors | |
MOSTLY_Q4_0 = 2 # except 1d tensors | |
MOSTLY_Q4_1 = 3 # except 1d tensors | |
# MOSTLY_Q4_1_SOME_F16 = 4 # tok_embeddings.weight and output.weight are F16 | |
# MOSTLY_Q4_2 = 5 # support has been removed | |
# MOSTLY_Q4_3 = 6 # support has been removed | |
MOSTLY_Q8_0 = 7 # except 1d tensors | |
MOSTLY_Q5_0 = 8 # except 1d tensors | |
MOSTLY_Q5_1 = 9 # except 1d tensors | |
MOSTLY_Q2_K = 10 # except 1d tensors | |
MOSTLY_Q3_K_S = 11 # except 1d tensors | |
MOSTLY_Q3_K_M = 12 # except 1d tensors | |
MOSTLY_Q3_K_L = 13 # except 1d tensors | |
MOSTLY_Q4_K_S = 14 # except 1d tensors | |
MOSTLY_Q4_K_M = 15 # except 1d tensors | |
MOSTLY_Q5_K_S = 16 # except 1d tensors | |
MOSTLY_Q5_K_M = 17 # except 1d tensors | |
MOSTLY_Q6_K = 18 # except 1d tensors | |
MOSTLY_IQ2_XXS = 19 # except 1d tensors | |
MOSTLY_IQ2_XS = 20 # except 1d tensors | |
MOSTLY_Q2_K_S = 21 # except 1d tensors | |
MOSTLY_IQ3_XS = 22 # except 1d tensors | |
MOSTLY_IQ3_XXS = 23 # except 1d tensors | |
MOSTLY_IQ1_S = 24 # except 1d tensors | |
MOSTLY_IQ4_NL = 25 # except 1d tensors | |
MOSTLY_IQ3_S = 26 # except 1d tensors | |
MOSTLY_IQ3_M = 27 # except 1d tensors | |
MOSTLY_IQ2_S = 28 # except 1d tensors | |
MOSTLY_IQ2_M = 29 # except 1d tensors | |
MOSTLY_IQ4_XS = 30 # except 1d tensors | |
MOSTLY_IQ1_M = 31 # except 1d tensors | |
MOSTLY_BF16 = 32 # except 1d tensors | |
MOSTLY_Q4_0_4_4 = 33 # except 1d tensors | |
MOSTLY_Q4_0_4_8 = 34 # except 1d tensors | |
MOSTLY_Q4_0_8_8 = 35 # except 1d tensors | |
MOSTLY_TQ1_0 = 36 # except 1d tensors | |
MOSTLY_TQ2_0 = 37 # except 1d tensors | |
GUESSED = 1024 # not specified in the model file | |
class GGUFEndian(IntEnum): | |
LITTLE = 0 | |
BIG = 1 | |
class GGUFValueType(IntEnum): | |
UINT8 = 0 | |
INT8 = 1 | |
UINT16 = 2 | |
INT16 = 3 | |
UINT32 = 4 | |
INT32 = 5 | |
FLOAT32 = 6 | |
BOOL = 7 | |
STRING = 8 | |
ARRAY = 9 | |
UINT64 = 10 | |
INT64 = 11 | |
FLOAT64 = 12 | |
def get_type(val: Any) -> GGUFValueType: | |
if isinstance(val, (str, bytes, bytearray)): | |
return GGUFValueType.STRING | |
elif isinstance(val, list): | |
return GGUFValueType.ARRAY | |
elif isinstance(val, float): | |
return GGUFValueType.FLOAT32 | |
elif isinstance(val, bool): | |
return GGUFValueType.BOOL | |
elif isinstance(val, int): | |
return GGUFValueType.INT32 | |
# TODO: need help with 64-bit types in Python | |
else: | |
raise ValueError(f"Unknown type: {type(val)}") | |
# Items here are (block size, type size) | |
QK_K = 256 | |
GGML_QUANT_SIZES: dict[GGMLQuantizationType, tuple[int, int]] = { | |
GGMLQuantizationType.F32: (1, 4), | |
GGMLQuantizationType.F16: (1, 2), | |
GGMLQuantizationType.Q4_0: (32, 2 + 16), | |
GGMLQuantizationType.Q4_1: (32, 2 + 2 + 16), | |
GGMLQuantizationType.Q5_0: (32, 2 + 4 + 16), | |
GGMLQuantizationType.Q5_1: (32, 2 + 2 + 4 + 16), | |
GGMLQuantizationType.Q8_0: (32, 2 + 32), | |
GGMLQuantizationType.Q8_1: (32, 4 + 4 + 32), | |
GGMLQuantizationType.Q2_K: (256, 2 + 2 + QK_K // 16 + QK_K // 4), | |
GGMLQuantizationType.Q3_K: (256, 2 + QK_K // 4 + QK_K // 8 + 12), | |
GGMLQuantizationType.Q4_K: (256, 2 + 2 + QK_K // 2 + 12), | |
GGMLQuantizationType.Q5_K: (256, 2 + 2 + QK_K // 2 + QK_K // 8 + 12), | |
GGMLQuantizationType.Q6_K: (256, 2 + QK_K // 2 + QK_K // 4 + QK_K // 16), | |
GGMLQuantizationType.Q8_K: (256, 4 + QK_K + QK_K // 8), | |
GGMLQuantizationType.IQ2_XXS: (256, 2 + QK_K // 4), | |
GGMLQuantizationType.IQ2_XS: (256, 2 + QK_K // 4 + QK_K // 32), | |
GGMLQuantizationType.IQ3_XXS: (256, 2 + QK_K // 4 + QK_K // 8), | |
GGMLQuantizationType.IQ1_S: (256, 2 + QK_K // 8 + QK_K // 16), | |
GGMLQuantizationType.IQ4_NL: (32, 2 + 16), | |
GGMLQuantizationType.IQ3_S: (256, 2 + QK_K // 4 + QK_K // 8 + QK_K // 32 + 4), | |
GGMLQuantizationType.IQ2_S: (256, 2 + QK_K // 4 + QK_K // 16), | |
GGMLQuantizationType.IQ4_XS: (256, 2 + 2 + QK_K // 2 + QK_K // 64), | |
GGMLQuantizationType.I8: (1, 1), | |
GGMLQuantizationType.I16: (1, 2), | |
GGMLQuantizationType.I32: (1, 4), | |
GGMLQuantizationType.I64: (1, 8), | |
GGMLQuantizationType.F64: (1, 8), | |
GGMLQuantizationType.IQ1_M: (256, QK_K // 8 + QK_K // 16 + QK_K // 32), | |
GGMLQuantizationType.BF16: (1, 2), | |
GGMLQuantizationType.Q4_0_4_4:(32, 2 + 16), | |
GGMLQuantizationType.Q4_0_4_8:(32, 2 + 16), | |
GGMLQuantizationType.Q4_0_8_8:(32, 2 + 16), | |
GGMLQuantizationType.TQ1_0: (256, 2 + 4 * 13), | |
GGMLQuantizationType.TQ2_0: (256, 2 + 64), | |
} | |
# Aliases for backward compatibility. | |
# general | |
KEY_GENERAL_ARCHITECTURE = Keys.General.ARCHITECTURE | |
KEY_GENERAL_QUANTIZATION_VERSION = Keys.General.QUANTIZATION_VERSION | |
KEY_GENERAL_ALIGNMENT = Keys.General.ALIGNMENT | |
KEY_GENERAL_NAME = Keys.General.NAME | |
KEY_GENERAL_AUTHOR = Keys.General.AUTHOR | |
KEY_GENERAL_URL = Keys.General.URL | |
KEY_GENERAL_DESCRIPTION = Keys.General.DESCRIPTION | |
KEY_GENERAL_LICENSE = Keys.General.LICENSE | |
KEY_GENERAL_SOURCE_URL = Keys.General.SOURCE_URL | |
KEY_GENERAL_FILE_TYPE = Keys.General.FILE_TYPE | |
# LLM | |
KEY_VOCAB_SIZE = Keys.LLM.VOCAB_SIZE | |
KEY_CONTEXT_LENGTH = Keys.LLM.CONTEXT_LENGTH | |
KEY_EMBEDDING_LENGTH = Keys.LLM.EMBEDDING_LENGTH | |
KEY_BLOCK_COUNT = Keys.LLM.BLOCK_COUNT | |
KEY_FEED_FORWARD_LENGTH = Keys.LLM.FEED_FORWARD_LENGTH | |
KEY_USE_PARALLEL_RESIDUAL = Keys.LLM.USE_PARALLEL_RESIDUAL | |
KEY_TENSOR_DATA_LAYOUT = Keys.LLM.TENSOR_DATA_LAYOUT | |
# attention | |
KEY_ATTENTION_HEAD_COUNT = Keys.Attention.HEAD_COUNT | |
KEY_ATTENTION_HEAD_COUNT_KV = Keys.Attention.HEAD_COUNT_KV | |
KEY_ATTENTION_MAX_ALIBI_BIAS = Keys.Attention.MAX_ALIBI_BIAS | |
KEY_ATTENTION_CLAMP_KQV = Keys.Attention.CLAMP_KQV | |
KEY_ATTENTION_LAYERNORM_EPS = Keys.Attention.LAYERNORM_EPS | |
KEY_ATTENTION_LAYERNORM_RMS_EPS = Keys.Attention.LAYERNORM_RMS_EPS | |
# RoPE | |
KEY_ROPE_DIMENSION_COUNT = Keys.Rope.DIMENSION_COUNT | |
KEY_ROPE_FREQ_BASE = Keys.Rope.FREQ_BASE | |
KEY_ROPE_SCALING_TYPE = Keys.Rope.SCALING_TYPE | |
KEY_ROPE_SCALING_FACTOR = Keys.Rope.SCALING_FACTOR | |
KEY_ROPE_SCALING_ORIG_CTX_LEN = Keys.Rope.SCALING_ORIG_CTX_LEN | |
KEY_ROPE_SCALING_FINETUNED = Keys.Rope.SCALING_FINETUNED | |
# SSM | |
KEY_SSM_CONV_KERNEL = Keys.SSM.CONV_KERNEL | |
KEY_SSM_INNER_SIZE = Keys.SSM.INNER_SIZE | |
KEY_SSM_STATE_SIZE = Keys.SSM.STATE_SIZE | |
KEY_SSM_TIME_STEP_RANK = Keys.SSM.TIME_STEP_RANK | |
KEY_SSM_DT_B_C_RMS = Keys.SSM.DT_B_C_RMS | |
# tokenization | |
KEY_TOKENIZER_MODEL = Keys.Tokenizer.MODEL | |
KEY_TOKENIZER_PRE = Keys.Tokenizer.PRE | |
KEY_TOKENIZER_LIST = Keys.Tokenizer.LIST | |
KEY_TOKENIZER_TOKEN_TYPE = Keys.Tokenizer.TOKEN_TYPE | |
KEY_TOKENIZER_SCORES = Keys.Tokenizer.SCORES | |
KEY_TOKENIZER_MERGES = Keys.Tokenizer.MERGES | |
KEY_TOKENIZER_BOS_ID = Keys.Tokenizer.BOS_ID | |
KEY_TOKENIZER_EOS_ID = Keys.Tokenizer.EOS_ID | |
KEY_TOKENIZER_EOT_ID = Keys.Tokenizer.EOT_ID | |
KEY_TOKENIZER_EOM_ID = Keys.Tokenizer.EOM_ID | |
KEY_TOKENIZER_UNK_ID = Keys.Tokenizer.UNK_ID | |
KEY_TOKENIZER_SEP_ID = Keys.Tokenizer.SEP_ID | |
KEY_TOKENIZER_PAD_ID = Keys.Tokenizer.PAD_ID | |
KEY_TOKENIZER_CLS_ID = Keys.Tokenizer.CLS_ID | |
KEY_TOKENIZER_MASK_ID = Keys.Tokenizer.MASK_ID | |
KEY_TOKENIZER_HF_JSON = Keys.Tokenizer.HF_JSON | |
KEY_TOKENIZER_RWKV = Keys.Tokenizer.RWKV | |
KEY_TOKENIZER_FIM_PRE_ID = Keys.Tokenizer.FIM_PRE_ID | |
KEY_TOKENIZER_FIM_SUF_ID = Keys.Tokenizer.FIM_SUF_ID | |
KEY_TOKENIZER_FIM_MID_ID = Keys.Tokenizer.FIM_MID_ID | |
KEY_TOKENIZER_FIM_PAD_ID = Keys.Tokenizer.FIM_PAD_ID | |
KEY_TOKENIZER_FIM_REP_ID = Keys.Tokenizer.FIM_REP_ID | |
KEY_TOKENIZER_FIM_SEP_ID = Keys.Tokenizer.FIM_SEP_ID | |
# deprecated | |
KEY_TOKENIZER_PREFIX_ID = Keys.Tokenizer.PREFIX_ID | |
KEY_TOKENIZER_SUFFIX_ID = Keys.Tokenizer.SUFFIX_ID | |
KEY_TOKENIZER_MIDDLE_ID = Keys.Tokenizer.MIDDLE_ID | |