constants : remove unneeded type annotations
This commit is contained in:
Jared Van Bortel
parent
5608cd8d89
commit
795dc0f048
1 changed files with 115 additions and 115 deletions
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@ -18,59 +18,59 @@ GGUF_DEFAULT_ALIGNMENT = 32
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class GeneralKeys(StrEnum):
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ARCHITECTURE: str = "general.architecture"
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QUANTIZATION_VERSION: str = "general.quantization_version"
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ALIGNMENT: str = "general.alignment"
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NAME: str = "general.name"
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AUTHOR: str = "general.author"
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URL: str = "general.url"
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DESCRIPTION: str = "general.description"
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LICENSE: str = "general.license"
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SOURCE_URL: str = "general.source.url"
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SOURCE_HF_REPO: str = "general.source.huggingface.repository"
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FILE_TYPE: str = "general.file_type"
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ARCHITECTURE = "general.architecture"
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QUANTIZATION_VERSION = "general.quantization_version"
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ALIGNMENT = "general.alignment"
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NAME = "general.name"
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AUTHOR = "general.author"
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URL = "general.url"
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DESCRIPTION = "general.description"
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LICENSE = "general.license"
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SOURCE_URL = "general.source.url"
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SOURCE_HF_REPO = "general.source.huggingface.repository"
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FILE_TYPE = "general.file_type"
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class AttentionKeys(StrEnum):
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HEAD_COUNT: str = "{arch}.attention.head_count"
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HEAD_COUNT_KV: str = "{arch}.attention.head_count_kv"
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MAX_ALIBI_BIAS: str = "{arch}.attention.max_alibi_bias"
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CLAMP_KQV: str = "{arch}.attention.clamp_kqv"
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LAYERNORM_EPS: str = "{arch}.attention.layer_norm_epsilon"
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LAYERNORM_RMS_EPS: str = "{arch}.attention.layer_norm_rms_epsilon"
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HEAD_COUNT = "{arch}.attention.head_count"
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HEAD_COUNT_KV = "{arch}.attention.head_count_kv"
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MAX_ALIBI_BIAS = "{arch}.attention.max_alibi_bias"
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CLAMP_KQV = "{arch}.attention.clamp_kqv"
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LAYERNORM_EPS = "{arch}.attention.layer_norm_epsilon"
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LAYERNORM_RMS_EPS = "{arch}.attention.layer_norm_rms_epsilon"
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class RopeKeys(StrEnum):
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DIMENSION_COUNT: str = "{arch}.rope.dimension_count"
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FREQ_BASE: str = "{arch}.rope.freq_base"
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SCALING_TYPE: str = "{arch}.rope.scaling.type"
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SCALING_FACTOR: str = "{arch}.rope.scaling.factor"
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SCALING_ORIG_CTX_LEN: str = "{arch}.rope.scaling.original_context_length"
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SCALING_FINETUNED: str = "{arch}.rope.scaling.finetuned"
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DIMENSION_COUNT = "{arch}.rope.dimension_count"
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FREQ_BASE = "{arch}.rope.freq_base"
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SCALING_TYPE = "{arch}.rope.scaling.type"
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SCALING_FACTOR = "{arch}.rope.scaling.factor"
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SCALING_ORIG_CTX_LEN = "{arch}.rope.scaling.original_context_length"
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SCALING_FINETUNED = "{arch}.rope.scaling.finetuned"
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class TokenizerKeys(StrEnum):
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MODEL: str = "tokenizer.ggml.model"
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LIST: str = "tokenizer.ggml.tokens"
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TOKEN_TYPE: str = "tokenizer.ggml.token_type"
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SCORES: str = "tokenizer.ggml.scores"
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MERGES: str = "tokenizer.ggml.merges"
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BOS_ID: str = "tokenizer.ggml.bos_token_id"
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EOS_ID: str = "tokenizer.ggml.eos_token_id"
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UNK_ID: str = "tokenizer.ggml.unknown_token_id"
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SEP_ID: str = "tokenizer.ggml.seperator_token_id"
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PAD_ID: str = "tokenizer.ggml.padding_token_id"
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HF_JSON: str = "tokenizer.huggingface.json"
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RWKV: str = "tokenizer.rwkv.world"
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MODEL = "tokenizer.ggml.model"
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LIST = "tokenizer.ggml.tokens"
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TOKEN_TYPE = "tokenizer.ggml.token_type"
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SCORES = "tokenizer.ggml.scores"
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MERGES = "tokenizer.ggml.merges"
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BOS_ID = "tokenizer.ggml.bos_token_id"
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EOS_ID = "tokenizer.ggml.eos_token_id"
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UNK_ID = "tokenizer.ggml.unknown_token_id"
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SEP_ID = "tokenizer.ggml.seperator_token_id"
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PAD_ID = "tokenizer.ggml.padding_token_id"
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HF_JSON = "tokenizer.huggingface.json"
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RWKV = "tokenizer.rwkv.world"
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class LLMKeys(StrEnum):
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CONTEXT_LENGTH: str = "{arch}.context_length"
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EMBEDDING_LENGTH: str = "{arch}.embedding_length"
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BLOCK_COUNT: str = "{arch}.block_count"
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FEED_FORWARD_LENGTH: str = "{arch}.feed_forward_length"
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USE_PARALLEL_RESIDUAL: str = "{arch}.use_parallel_residual"
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TENSOR_DATA_LAYOUT: str = "{arch}.tensor_data_layout"
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CONTEXT_LENGTH = "{arch}.context_length"
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EMBEDDING_LENGTH = "{arch}.embedding_length"
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BLOCK_COUNT = "{arch}.block_count"
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FEED_FORWARD_LENGTH = "{arch}.feed_forward_length"
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USE_PARALLEL_RESIDUAL = "{arch}.use_parallel_residual"
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TENSOR_DATA_LAYOUT = "{arch}.tensor_data_layout"
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class Keys:
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@ -87,42 +87,42 @@ class Keys:
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class MODEL_ARCH(IntEnum):
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LLAMA: int = auto()
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FALCON: int = auto()
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BAICHUAN: int = auto()
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GPT2: int = auto()
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GPTJ: int = auto()
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GPTNEOX: int = auto()
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MPT: int = auto()
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STARCODER: int = auto()
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PERSIMMON: int = auto()
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REFACT: int = auto()
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BERT: int = auto()
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BLOOM: int = auto()
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LLAMA = auto()
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FALCON = auto()
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BAICHUAN = auto()
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GPT2 = auto()
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GPTJ = auto()
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GPTNEOX = auto()
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MPT = auto()
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STARCODER = auto()
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PERSIMMON = auto()
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REFACT = auto()
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BERT = auto()
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BLOOM = auto()
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class MODEL_TENSOR(IntEnum):
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TOKEN_EMBD: int = auto()
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TOKEN_EMBD_NORM: int = auto()
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TOKEN_TYPES: int = auto()
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POS_EMBD: int = auto()
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OUTPUT: int = auto()
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OUTPUT_NORM: int = auto()
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ROPE_FREQS: int = auto()
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ATTN_Q: int = auto()
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ATTN_K: int = auto()
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ATTN_V: int = auto()
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ATTN_QKV: int = auto()
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ATTN_OUT: int = auto()
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ATTN_NORM: int = auto()
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ATTN_NORM_2: int = auto()
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ATTN_ROT_EMBD: int = auto()
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FFN_GATE: int = auto()
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FFN_DOWN: int = auto()
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FFN_UP: int = auto()
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FFN_NORM: int = auto()
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ATTN_Q_NORM: int = auto()
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ATTN_K_NORM: int = auto()
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TOKEN_EMBD = auto()
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TOKEN_EMBD_NORM = auto()
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TOKEN_TYPES = auto()
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POS_EMBD = auto()
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OUTPUT = auto()
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OUTPUT_NORM = auto()
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ROPE_FREQS = auto()
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ATTN_Q = auto()
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ATTN_K = auto()
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ATTN_V = auto()
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ATTN_QKV = auto()
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ATTN_OUT = auto()
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ATTN_NORM = auto()
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ATTN_NORM_2 = auto()
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ATTN_ROT_EMBD = auto()
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FFN_GATE = auto()
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FFN_DOWN = auto()
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FFN_UP = auto()
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FFN_NORM = auto()
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ATTN_Q_NORM = auto()
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ATTN_K_NORM = auto()
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MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
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@ -428,52 +428,52 @@ GGML_QUANT_SIZES = {
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# Aliases for backward compatibility.
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# general
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KEY_GENERAL_ARCHITECTURE: str = Keys.GENERAL.ARCHITECTURE
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KEY_GENERAL_QUANTIZATION_VERSION: str = Keys.GENERAL.QUANTIZATION_VERSION
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KEY_GENERAL_ALIGNMENT: str = Keys.GENERAL.ALIGNMENT
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KEY_GENERAL_NAME: str = Keys.GENERAL.NAME
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KEY_GENERAL_AUTHOR: str = Keys.GENERAL.AUTHOR
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KEY_GENERAL_URL: str = Keys.GENERAL.URL
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KEY_GENERAL_DESCRIPTION: str = Keys.GENERAL.DESCRIPTION
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KEY_GENERAL_LICENSE: str = Keys.GENERAL.LICENSE
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KEY_GENERAL_SOURCE_URL: str = Keys.GENERAL.SOURCE_URL
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KEY_GENERAL_SOURCE_HF_REPO: str = Keys.GENERAL.SOURCE_HF_REPO
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KEY_GENERAL_FILE_TYPE: str = Keys.GENERAL.FILE_TYPE
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KEY_GENERAL_ARCHITECTURE = Keys.GENERAL.ARCHITECTURE
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KEY_GENERAL_QUANTIZATION_VERSION = Keys.GENERAL.QUANTIZATION_VERSION
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KEY_GENERAL_ALIGNMENT = Keys.GENERAL.ALIGNMENT
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KEY_GENERAL_NAME = Keys.GENERAL.NAME
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KEY_GENERAL_AUTHOR = Keys.GENERAL.AUTHOR
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KEY_GENERAL_URL = Keys.GENERAL.URL
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KEY_GENERAL_DESCRIPTION = Keys.GENERAL.DESCRIPTION
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KEY_GENERAL_LICENSE = Keys.GENERAL.LICENSE
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KEY_GENERAL_SOURCE_URL = Keys.GENERAL.SOURCE_URL
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KEY_GENERAL_SOURCE_HF_REPO = Keys.GENERAL.SOURCE_HF_REPO
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KEY_GENERAL_FILE_TYPE = Keys.GENERAL.FILE_TYPE
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# LLM
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KEY_CONTEXT_LENGTH: str = Keys.LLM.CONTEXT_LENGTH
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KEY_EMBEDDING_LENGTH: str = Keys.LLM.EMBEDDING_LENGTH
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KEY_BLOCK_COUNT: str = Keys.LLM.BLOCK_COUNT
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KEY_FEED_FORWARD_LENGTH: str = Keys.LLM.FEED_FORWARD_LENGTH
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KEY_USE_PARALLEL_RESIDUAL: str = Keys.LLM.USE_PARALLEL_RESIDUAL
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KEY_TENSOR_DATA_LAYOUT: str = Keys.LLM.TENSOR_DATA_LAYOUT
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KEY_CONTEXT_LENGTH = Keys.LLM.CONTEXT_LENGTH
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KEY_EMBEDDING_LENGTH = Keys.LLM.EMBEDDING_LENGTH
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KEY_BLOCK_COUNT = Keys.LLM.BLOCK_COUNT
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KEY_FEED_FORWARD_LENGTH = Keys.LLM.FEED_FORWARD_LENGTH
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KEY_USE_PARALLEL_RESIDUAL = Keys.LLM.USE_PARALLEL_RESIDUAL
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KEY_TENSOR_DATA_LAYOUT = Keys.LLM.TENSOR_DATA_LAYOUT
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# attention
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KEY_ATTENTION_HEAD_COUNT: str = Keys.ATTENTION.HEAD_COUNT
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KEY_ATTENTION_HEAD_COUNT_KV: str = Keys.ATTENTION.HEAD_COUNT_KV
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KEY_ATTENTION_MAX_ALIBI_BIAS: str = Keys.ATTENTION.MAX_ALIBI_BIAS
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KEY_ATTENTION_CLAMP_KQV: str = Keys.ATTENTION.CLAMP_KQV
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KEY_ATTENTION_LAYERNORM_EPS: str = Keys.ATTENTION.LAYERNORM_EPS
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KEY_ATTENTION_LAYERNORM_RMS_EPS: str = Keys.ATTENTION.LAYERNORM_RMS_EPS
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KEY_ATTENTION_HEAD_COUNT = Keys.ATTENTION.HEAD_COUNT
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KEY_ATTENTION_HEAD_COUNT_KV = Keys.ATTENTION.HEAD_COUNT_KV
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KEY_ATTENTION_MAX_ALIBI_BIAS = Keys.ATTENTION.MAX_ALIBI_BIAS
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KEY_ATTENTION_CLAMP_KQV = Keys.ATTENTION.CLAMP_KQV
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KEY_ATTENTION_LAYERNORM_EPS = Keys.ATTENTION.LAYERNORM_EPS
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KEY_ATTENTION_LAYERNORM_RMS_EPS = Keys.ATTENTION.LAYERNORM_RMS_EPS
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# RoPE
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KEY_ROPE_DIMENSION_COUNT: str = Keys.ROPE.DIMENSION_COUNT
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KEY_ROPE_FREQ_BASE: str = Keys.ROPE.FREQ_BASE
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KEY_ROPE_SCALING_TYPE: str = Keys.ROPE.SCALING_TYPE
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KEY_ROPE_SCALING_FACTOR: str = Keys.ROPE.SCALING_FACTOR
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KEY_ROPE_SCALING_ORIG_CTX_LEN: str = Keys.ROPE.SCALING_ORIG_CTX_LEN
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KEY_ROPE_SCALING_FINETUNED: str = Keys.ROPE.SCALING_FINETUNED
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KEY_ROPE_DIMENSION_COUNT = Keys.ROPE.DIMENSION_COUNT
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KEY_ROPE_FREQ_BASE = Keys.ROPE.FREQ_BASE
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KEY_ROPE_SCALING_TYPE = Keys.ROPE.SCALING_TYPE
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KEY_ROPE_SCALING_FACTOR = Keys.ROPE.SCALING_FACTOR
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KEY_ROPE_SCALING_ORIG_CTX_LEN = Keys.ROPE.SCALING_ORIG_CTX_LEN
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KEY_ROPE_SCALING_FINETUNED = Keys.ROPE.SCALING_FINETUNED
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# tokenization
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KEY_TOKENIZER_MODEL: str = Keys.TOKENIZER.MODEL
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KEY_TOKENIZER_LIST: str = Keys.TOKENIZER.LIST
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KEY_TOKENIZER_TOKEN_TYPE: str = Keys.TOKENIZER.TOKEN_TYPE
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KEY_TOKENIZER_SCORES: str = Keys.TOKENIZER.SCORES
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KEY_TOKENIZER_MERGES: str = Keys.TOKENIZER.MERGES
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KEY_TOKENIZER_BOS_ID: str = Keys.TOKENIZER.BOS_ID
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KEY_TOKENIZER_EOS_ID: str = Keys.TOKENIZER.EOS_ID
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KEY_TOKENIZER_UNK_ID: str = Keys.TOKENIZER.UNK_ID
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KEY_TOKENIZER_SEP_ID: str = Keys.TOKENIZER.SEP_ID
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KEY_TOKENIZER_PAD_ID: str = Keys.TOKENIZER.PAD_ID
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KEY_TOKENIZER_HF_JSON: str = Keys.TOKENIZER.HF_JSON
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KEY_TOKENIZER_RWKV: str = Keys.TOKENIZER.RWKV
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KEY_TOKENIZER_MODEL = Keys.TOKENIZER.MODEL
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KEY_TOKENIZER_LIST = Keys.TOKENIZER.LIST
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KEY_TOKENIZER_TOKEN_TYPE = Keys.TOKENIZER.TOKEN_TYPE
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KEY_TOKENIZER_SCORES = Keys.TOKENIZER.SCORES
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KEY_TOKENIZER_MERGES = Keys.TOKENIZER.MERGES
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KEY_TOKENIZER_BOS_ID = Keys.TOKENIZER.BOS_ID
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KEY_TOKENIZER_EOS_ID = Keys.TOKENIZER.EOS_ID
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KEY_TOKENIZER_UNK_ID = Keys.TOKENIZER.UNK_ID
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KEY_TOKENIZER_SEP_ID = Keys.TOKENIZER.SEP_ID
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KEY_TOKENIZER_PAD_ID = Keys.TOKENIZER.PAD_ID
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KEY_TOKENIZER_HF_JSON = Keys.TOKENIZER.HF_JSON
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KEY_TOKENIZER_RWKV = Keys.TOKENIZER.RWKV
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