T5CrossEncoderModel

class lightning_ir.models.t5.model.T5CrossEncoderModel(config: T5CrossEncoderConfig, *args, **kwargs)

Bases: CrossEncoderModel

__init__(config: T5CrossEncoderConfig, *args, **kwargs)

Methods

__init__(config, *args, **kwargs)
forward(encoding)
from_pretrained(model_name_or_path, *args, ...)	Loads a pretrained model. Wraps the transformers.PreTrainedModel.from_pretrained method and to return a

Attributes

ALLOW_SUB_BATCHING

Flag to allow mini batches of documents for a single query.

classmethod from_pretrained(model_name_or_path: str | Path, *args, **kwargs) → LightningIRModel

Loads a pretrained model. Wraps the transformers.PreTrainedModel.from_pretrained method and to return a

derived LightningIRModel. See LightningIRModelClassFactory for more details.

param model_name_or_path:

Name or path of the pretrained model

type model_name_or_path:

str | Path

raises ValueError:

If called on the abstract class LightningIRModel and no config is passed

return:

A derived LightningIRModel consisting of a backbone model and a LightningIRModel mixin

rtype:

LightningIRModel

>>> # Loading using model class and backbone checkpoint
>>> type(CrossEncoderModel.from_pretrained("bert-base-uncased"))
<class 'lightning_ir.base.class_factory.CrossEncoderBertModel'>
>>> # Loading using base class and backbone checkpoint
>>> type(LightningIRModel.from_pretrained("bert-base-uncased", config=CrossEncoderConfig()))
<class 'lightning_ir.base.class_factory.CrossEncoderBertModel'>