ColConfig
- class lightning_ir.models.col.ColConfig(query_expansion: bool = True, doc_mask_scoring_tokens: Sequence[str] | Literal['punctuation'] | None = 'punctuation', embedding_dim: int = 128, projection: Literal['linear', 'linear_no_bias'] | None = 'linear_no_bias', **kwargs)[source]
Bases:
BiEncoderConfig
- __init__(query_expansion: bool = True, doc_mask_scoring_tokens: Sequence[str] | Literal['punctuation'] | None = 'punctuation', embedding_dim: int = 128, projection: Literal['linear', 'linear_no_bias'] | None = 'linear_no_bias', **kwargs) None [source]
Methods
__init__
([query_expansion, ...])from_dict
(config_dict, *args, **kwargs)Loads the configuration from a dictionary.
from_pretrained
(...)get_config_dict
(...)save_pretrained
(save_directory[, push_to_hub])Outputs a dictionary of the added arguments.
to_dict
()Outputs a dictionary of the tokenizer arguments.
Attributes
ADDED_ARGS
Arguments added to the configuration.
TOKENIZER_ARGS
Arguments for the tokenizer.
backbone_model_type
Backbone model type for the configuration.
model_type
Model type for the configuration.
- classmethod from_dict(config_dict: Dict[str, Any], *args, **kwargs) LightningIRConfig
Loads the configuration from a dictionary. Wraps the transformers.PretrainedConfig.from_dict method to return a derived LightningIRConfig class. See
LightningIRConfigClassFactory
for more details.- Parameters:
config_dict (Dict[str, Any]) – Configuration dictionary
- Raises:
ValueError – If the model type does not match the configuration model type
- Returns:
Derived LightningIRConfig class
- Return type: