MonoConfig

class lightning_ir.models.cross_encoders.mono.MonoConfig(query_length: int | None = 32, doc_length: int | None = 512, pooling_strategy: 'first' | 'mean' | 'max' | 'sum' | 'bert_pool' = 'first', linear_bias: bool = False, scoring_strategy: 'mono' | 'rank' = 'rank', tokenizer_pattern: str | None = None, **kwargs)[source]

Bases: CrossEncoderConfig

Configuration class for mono cross-encoder models.

__init__(query_length: int | None = 32, doc_length: int | None = 512, pooling_strategy: 'first' | 'mean' | 'max' | 'sum' | 'bert_pool' = 'first', linear_bias: bool = False, scoring_strategy: 'mono' | 'rank' = 'rank', tokenizer_pattern: str | None = None, **kwargs)[source]

Initialize the configuration for mono cross-encoder models.

Parameters:

  • query_length (int | None) – Maximum number of tokens per query. If None does not truncate. Defaults to 32.

  • doc_length (int | None) – Maximum number of tokens per document. If None does not truncate. Defaults to 512.

  • pooling_strategy (Literal["first", "mean", "max", "sum", "bert_pool"]) – Pooling strategy for the embeddings. Defaults to “first”.

  • linear_bias (bool) – Whether to use bias in the final linear layer. Defaults to False.

  • scoring_strategy (Literal["mono", "rank"]) – Scoring strategy to use. Defaults to “rank”.

  • tokenizer_pattern (str | None) – Optional pattern for tokenization. Defaults to None.

Methods

__init__([query_length, doc_length, ...])

Initialize the configuration for mono cross-encoder models.

Attributes

model_type

Model type for mono cross-encoder models.
model_type: str = 'mono'

Model type for mono cross-encoder models.