medcat.components.addons.relation_extraction.llama.config

Classes:

• RelExtrLlamaConfig –

  Class for LlamaConfig

Attributes:

• logger –

logger module-attribute

logger = getLogger(__name__)

RelExtrLlamaConfig

RelExtrLlamaConfig(pretrained_model_name_or_path, **kwargs)

Bases: RelExtrBaseConfig

Class for LlamaConfig

Methods:

• load –

Attributes:

• hf_model_config (LlamaConfig) –
• name –
• pretrained_model_name_or_path –

Source code in medcat-v2/medcat/components/addons/relation_extraction/config.py

def __init__(self, pretrained_model_name_or_path, **kwargs):
    super().__init__(**kwargs)
    self.model_type = "relcat"
    self.pretrained_model_name_or_path = pretrained_model_name_or_path
    self.hf_model_config: PretrainedConfig = kwargs.get(
        "model_config", PretrainedConfig())

hf_model_config instance-attribute

hf_model_config: LlamaConfig

name class-attribute instance-attribute

name = 'llama-config'

pretrained_model_name_or_path class-attribute instance-attribute

pretrained_model_name_or_path = 'meta-llama/Llama-3.1-8B'

load classmethod

load(pretrained_model_name_or_path: str, relcat_config: ConfigRelCAT, **kwargs) -> RelExtrLlamaConfig

Source code in medcat-v2/medcat/components/addons/relation_extraction/llama/config.py

@classmethod
def load(cls, pretrained_model_name_or_path: str,
         relcat_config: ConfigRelCAT, **kwargs
         ) -> "RelExtrLlamaConfig":
    model_config = cls(pretrained_model_name_or_path, **kwargs)

    if pretrained_model_name_or_path and os.path.exists(
            pretrained_model_name_or_path):
        model_config.hf_model_config = cast(
            LlamaConfig, LlamaConfig.from_json_file(
                pretrained_model_name_or_path))
        logger.info("Loaded config from file: %s",
                    pretrained_model_name_or_path)
    else:
        pretrained_model = relcat_config.general.model_name = (
            cls.pretrained_model_name_or_path)
        model_config.hf_model_config = cast(
            LlamaConfig, LlamaConfig.from_pretrained(
                pretrained_model_name_or_path=pretrained_model, **kwargs))
        logger.info("Loaded config from pretrained: %s", pretrained_model)

    return model_config