T5CrossEncoderConfig

class lightning_ir.models.t5.config.T5CrossEncoderConfig(query_length: int = 32, doc_length: int = 512, decoder_strategy: Literal['mono', 'rank'] = 'mono', **kwargs)

Bases: CrossEncoderConfig

__init__(query_length: int = 32, doc_length: int = 512, decoder_strategy: Literal['mono', 'rank'] = 'mono', **kwargs) → None

Methods

__init__([query_length, doc_length, ...])
from_dict(config_dict, *args, **kwargs)	Loads the configuration from a dictionary.
from_pretrained(...)
to_added_args_dict()	Outputs a dictionary of the added arguments.
to_dict()	Overrides the transformers.PretrainedConfig.to_dict method to include the added arguments and the backbone model type.
to_tokenizer_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:

LightningIRConfig

to_added_args_dict() → Dict[str, Any]

Outputs a dictionary of the added arguments.

Returns:

Added arguments

Return type:

Dict[str, Any]

to_dict() → Dict[str, Any]

Overrides the transformers.PretrainedConfig.to_dict method to include the added arguments and the backbone model type.

Returns:

Configuration dictionary

Return type:

Dict[str, Any]

to_tokenizer_dict() → Dict[str, Any]

Outputs a dictionary of the tokenizer arguments.

Returns:

Tokenizer arguments

Return type:

Dict[str, Any]