fix dataclass init
This commit is contained in:
jeromeku
parent
16fd50daeb
commit
72da9ffd34
2 changed files with 105 additions and 54 deletions
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@ -19,7 +19,9 @@ _IS_PHI_REGISTERED = False
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_IS_PHI_INSTRUCT_REGISTERED = False
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def construct_model_key(org, base_name, version, size, quant_type, instruct_tag):
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def construct_model_key(
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org, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{org}/{base_name}-{version}-{size}B"
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if instruct_tag:
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key = "-".join([key, instruct_tag])
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@ -58,7 +60,9 @@ class ModelInfo:
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return key
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@staticmethod
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def append_quant_type(key: str, quant_type: Literal["bnb", "unsloth"] = None):
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def append_quant_type(
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key: str, quant_type: Literal["bnb", "unsloth"] = None
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):
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if quant_type:
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if quant_type == "bnb":
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key = "-".join([key, BNB_QUANTIZED_TAG])
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@ -67,7 +71,9 @@ class ModelInfo:
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return key
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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raise NotImplementedError("Subclass must implement this method")
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@property
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@ -79,7 +85,9 @@ class ModelInfo:
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class LlamaModelInfo(ModelInfo):
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{base_name}-{version}-{size}B"
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key = cls.append_instruct_tag(key, instruct_tag)
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key = cls.append_quant_type(key, quant_type)
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@ -88,7 +96,9 @@ class LlamaModelInfo(ModelInfo):
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class LlamaVisionModelInfo(ModelInfo):
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{base_name}-{version}-{size}B-Vision"
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key = cls.append_instruct_tag(key, instruct_tag)
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key = cls.append_quant_type(key, quant_type)
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@ -97,7 +107,9 @@ class LlamaVisionModelInfo(ModelInfo):
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class QwenModelInfo(ModelInfo):
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{base_name}{version}-{size}B"
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key = cls.append_instruct_tag(key, instruct_tag)
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key = cls.append_quant_type(key, quant_type)
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@ -106,7 +118,9 @@ class QwenModelInfo(ModelInfo):
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class QwenVLModelInfo(ModelInfo):
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{base_name}{version}-VL-{size}B"
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key = cls.append_instruct_tag(key, instruct_tag)
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key = cls.append_quant_type(key, quant_type)
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@ -115,58 +129,62 @@ class QwenVLModelInfo(ModelInfo):
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class PhiModelInfo(ModelInfo):
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@classmethod
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def construct_model_name(cls, base_name, version, size, quant_type, instruct_tag):
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def construct_model_name(
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cls, base_name, version, size, quant_type, instruct_tag
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):
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key = f"{base_name}-{version}"
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key = cls.append_instruct_tag(key, instruct_tag)
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key = cls.append_quant_type(key, quant_type)
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return key
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@dataclass
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class ModelMetaBase:
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class ModelMeta:
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org: str
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base_name: str
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@dataclass
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class ModelMeta(ModelMetaBase):
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instruct_tags: list[str]
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model_version: str
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model_sizes: list[str]
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is_multimodal: bool
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model_info_cls: type[ModelInfo]
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quant_types: list[Literal[None, "bnb", "unsloth", "GGUF"]]
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@dataclass
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class LlamaMetaBase(ModelMetaBase):
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org: str = "meta-llama"
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base_name: str = "Llama"
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@dataclass
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class LlamaMeta3_1(LlamaMetaBase, ModelMeta):
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instruct_tags: list[str] = [None, "Instruct"]
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model_version: str = "3.1"
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model_sizes: list[str] = [8]
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model_sizes: list[str] = field(default_factory=list)
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instruct_tags: list[str] = field(default_factory=list)
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quant_types: list[Literal[None, "bnb", "unsloth"]] = field(
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default_factory=list
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)
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is_multimodal: bool = False
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quant_types: list[Literal[None, "bnb", "unsloth"]] = [None]
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model_info_cls: type[ModelInfo] = LlamaModelInfo
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@dataclass
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class LlamaMeta3_2(LlamaMetaBase, ModelMeta):
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instruct_tags: list[str] = [None, "Instruct"]
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model_version: str = "3.2"
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model_sizes: list[str] = [1, 3]
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is_multimodal: bool = False
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quant_types: list[Literal[None, "bnb", "unsloth"]] = [None]
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model_info_cls: type[ModelInfo] = LlamaModelInfo
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# Llama text only models
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_LLAMA_INFO = {
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"org": "meta-llama",
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"base_name": "Llama",
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"instruct_tags": [None, "Instruct"],
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"model_versions": ["3.2", "3.1"],
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"model_sizes": {"3.2": [1, 3], "3.1": [8]},
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"is_multimodal": False,
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"model_info_cls": LlamaModelInfo,
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}
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LlamaMeta3_1 = ModelMeta(
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org="meta-llama",
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base_name="Llama",
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instruct_tags=[None, "Instruct"],
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model_version="3.1",
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model_sizes=[8],
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model_info_cls=LlamaModelInfo,
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is_multimodal=False,
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quant_types=[None, "bnb", "unsloth"],
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)
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LlamaMeta3_2 = ModelMeta(
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org="meta-llama",
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base_name="Llama",
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instruct_tags=[None, "Instruct"],
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model_version="3.2",
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model_sizes=[1, 3],
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model_info_cls=LlamaModelInfo,
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is_multimodal=False,
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quant_types=[None, "bnb", "unsloth"],
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)
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# # Llama text only models
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# _LLAMA_INFO = {
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# "org": "meta-llama",
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# "base_name": "Llama",
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# "instruct_tags": [None, "Instruct"],
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# "model_versions": ["3.2", "3.1"],
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# "model_sizes": {"3.2": [1, 3], "3.1": [8]},
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# "is_multimodal": False,
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# "model_info_cls": LlamaModelInfo,
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# }
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_LLAMA_VISION_INFO = {
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"org": "meta-llama",
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@ -293,6 +311,7 @@ def register_model(
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# is_multimodal=is_multimodal,
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# )
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def _register_models(model_meta: ModelMeta):
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org = model_meta.org
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base_name = model_meta.base_name
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@ -318,6 +337,7 @@ def _register_models(model_meta: ModelMeta):
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is_multimodal=is_multimodal,
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)
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def register_llama_models():
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global _IS_LLAMA_REGISTERED
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if _IS_LLAMA_REGISTERED:
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@ -387,7 +407,9 @@ def get_llama_models():
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if not _IS_LLAMA_REGISTERED:
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register_llama_models()
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return _get_models(partial(_base_name_filter, base_name=_LLAMA_INFO["base_name"]))
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return _get_models(
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partial(_base_name_filter, base_name=_LLAMA_INFO["base_name"])
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)
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def get_llama_vision_models():
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@ -395,7 +417,8 @@ def get_llama_vision_models():
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register_llama_vision_models()
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return _get_models(
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lambda model_info: model_info.base_name == _LLAMA_VISION_INFO["base_name"]
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lambda model_info: model_info.base_name
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== _LLAMA_VISION_INFO["base_name"]
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and model_info.is_multimodal
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)
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@ -438,12 +461,34 @@ def get_phi_instruct_models():
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if not _IS_PHI_INSTRUCT_REGISTERED:
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register_phi_instruct_models()
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return _get_models(
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lambda model_info: model_info.base_name == _PHI_INSTRUCT_INFO["base_name"]
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lambda model_info: model_info.base_name
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== _PHI_INSTRUCT_INFO["base_name"]
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)
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if __name__ == "__main__":
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register_llama_models()
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from huggingface_hub import HfApi
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api = HfApi()
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def get_model_info(
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model_id: str, properties: list[str] = None
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) -> ModelInfo:
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try:
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model_info: ModelInfo = api.model_info(model_id, expand=properties)
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except Exception as e:
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print(f"Error getting model info for {model_id}: {e}")
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model_info = None
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return model_info
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test_model = LlamaMeta3_2
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_register_models(test_model)
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for k, v in MODEL_REGISTRY.items():
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print(f"{k}: {v}")
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print(v.model_path)
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model_info = get_model_info(v.model_path)
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if model_info is None:
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# print unicode cross mark followed by model k
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print(f"\u2718 {k}")
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else:
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# print unicode checkmark followed by model k
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print(f"\u2713 {k} found")
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@ -1,6 +1,6 @@
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from huggingface_hub import HfApi, ModelInfo
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api = HfApi()
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api: HfApi
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POPULARITY_PROPERTIES = [
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"downloads",
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@ -32,6 +32,9 @@ def get_model_info(
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Default properties: ["safetensors", "lastModified"], only retrieves minimal information.
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Set to None to retrieve the full model information.
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"""
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global api
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if api is None:
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api = HfApi()
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try:
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model_info: ModelInfo = api.model_info(model_id, expand=properties)
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except Exception as e:
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@ -58,6 +61,9 @@ def retrieve_models(
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search: str = The search query for filtering models.
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"""
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global api
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if api is None:
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api = HfApi()
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if full:
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properties = None
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