(self, sentences: Union[List[str], str], is_query: bool = False, instruction=None, dim: int = -1)

( self, sentences: Sequence[str], max_length: int, prompt: str | None = None

(self, sentences: Union[List[str], str], is_query: bool = False, instruction=None, dim: int = -1)

(self, **kwargs)

(self, **kwargs)

(t, model, args, **kwargs)

(self)

(self)

( self, model: str, use_instruction: bool = False, device: str = 'cuda',

(self, inputs, **kwargs)

(self, pairs, **kwargs)

( self, pairs, instruction=None, **kwargs )

( self, sentences: Sequence[str], *, task_name: str, prompt_type: Prom

(self, instruction, query, doc)

(self, instruction, query, doc)

(self, instruction, prompt_type)

(self, instruction, query, doc)

( self, input_ids: torch.LongTensor, attention_mask: torch.Tensor, **kwargs

(self, task_description: str, query: str)

(self, task_description: str, query: str)

(self, task_name, prompt_type)

(model_path: str, model_name: str, precision: str = 'fp16', **kwargs)

(model_name: str, precision: str = 'fp16', **kwargs)

(names: list[str] | None, languages: list[str] | None = None, benchmark: str | None = None)

(names: list[str] | None, languages: list[str] | None = None, benchmark: str | None = None)

(names: list[str] | None, languages: list[str] | None = None, benchmark: str | None = None)

(self, last_hidden_states: Tensor, attention_mask: Tensor)

()

()

(self, pairs, **kwargs)

(self, pairs)

(model, tasks: list, args: EvalArguments, **kwargs)

(model, tasks: list, args: EvalArguments, **kwargs)

(self)

(self)

(self, texts, max_length: int, prompt=None)

(self, model_name_or_path, instruction=None, use_fp16: bool = True, use_cuda: bool = True, max_length=8192)

(self, model_name_or_path, instruction="Given the user query, retrieval the relevant passages", **kwargs)

(self, model_name_or_path, instruction=None, max_length=8192)

( self, model_name_or_path: str, max_length: int = 4096, instruction=None,

( self, model: str, pooler_type: str = 'last', do_norm: bool = False,

(self, model_name, instruction="Given the user query, retrieval the relevant passages", **kwargs)

(self)

(self)

( model: TransformersTextEmbedder, input_queue, output_queue, device: torch.device, qsize:

( self, retriever, corpus, queries, relevant_docs, hf_subset: str, **kwargs )

(self)

(self)

(self)

(self)

(self)

(self)

(self)

(hidden_state: torch.Tensor, _)

(hidden_state: torch.Tensor, attention_mask: torch.Tensor)

(hidden_state: torch.Tensor, _)

(hidden_state: torch.Tensor, attention_mask: torch.Tensor)

(hidden_state: torch.Tensor, attention_mask: torch.Tensor)

(oq, timeout=0.00125)

( self, model, split: str = "test", subsets_to_run: list | None = None, *, encode_kwar

( self, sentences: list[tuple[str, str]] | list[list[str]], batch_size: int = None,

(self)

(self)