Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results
Inference Endpoints
File size: 984 Bytes
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from typing import Dict, List, Any
from InstructorEmbedding import INSTRUCTOR
class EndpointHandler:
def __init__(self, path=""):
# load model on gpu
self.model = INSTRUCTOR(path, device="cuda")
def __call__(self, data: Dict[str, Any]) -> List[List[float]]:
"""
data args:
inputs (:obj: `str`)
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
# get inputs
inputs: dict = data.pop("inputs", data)
texts = inputs.pop("texts", None)
instruction = inputs.pop("instruction", None)
if not texts or not instruction:
raise ValueError("Please provide texts and instruction")
# make sure texts is a list
if not isinstance(texts, list):
texts = [texts]
instructions = [[instruction, text] for text in texts]
embeddings = self.model.encode(instructions)
return embeddings.tolist()
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