Tony20100/langchain_full huggingface dataset:
langchain_community.cross_encoders.sagemaker_endpoint.CrossEncoderContentHandler¶
class langchain_community.cross_encoders.sagemaker_endpoint.CrossEncoderContentHandler[source]¶
Content handler for CrossEncoder class.
Attributes
accepts
content_type
Methods
__init__()
transform_input(text_pairs)
transform_output(output)
__init__()¶
transform_input(text_pairs: List[Tuple[str, str]]) → bytes[source]¶
Parameters
text_pairs (List[Tuple[str, str]]) – 
Return type
bytes
transform_output(output: Any) → List[float][source]¶
Parameters
output (Any) – 
Return type
List[float]
langchain_community.cross_encoders.huggingface.HuggingFaceCrossEncoder¶
class langchain_community.cross_encoders.huggingface.HuggingFaceCrossEncoder[source]¶
Bases: BaseModel, BaseCrossEncoder
HuggingFace cross encoder models.
Example
from langchain_community.cross_encoders import HuggingFaceCrossEncoder
model_name = "BAAI/bge-reranker-base"
model_kwargs = {'device': 'cpu'}
hf = HuggingFaceCrossEncoder(
    model_name=model_name,
    model_kwargs=model_kwargs
)
Initialize the sentence_transformer.
param model_kwargs: Dict[str, Any] [Optional]¶
Keyword arguments to pass to the model.
param model_name: str = 'BAAI/bge-reranker-base'¶
Model name to use.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
score(text_pairs: List[Tuple[str, str]]) → List[float][source]¶
Compute similarity scores using a HuggingFace transformer model.
Parameters
text_pairs (List[Tuple[str, str]]) – The list of text text_pairs to score the similarity.
Returns
List of scores, one for each pair.
Return type
List[float]
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using HuggingFaceCrossEncoder¶
Cross Encoder Reranker
langchain_community.cross_encoders.fake.FakeCrossEncoder¶
class langchain_community.cross_encoders.fake.FakeCrossEncoder[source]¶
Bases: BaseCrossEncoder, BaseModel
Fake cross encoder model.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
score(text_pairs: List[Tuple[str, str]]) → List[float][source]¶
Score pairs’ similarity.
Parameters
text_pairs (List[Tuple[str, str]]) – List of pairs of texts.
Returns
List of scores.
Return type
List[float]
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model