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import torch
from typing import Dict, Any, List
from transformers import pipeline
class EndpointHandler:
def __init__(
self,
path: str,
) -> None:
self.pipeline = pipeline(model=path, torch_dtype=torch.bfloat16, trust_remote_code=True, return_full_text=True)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str`)
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
inputs = data.pop("inputs", data)
parameters = data.pop("parameters", None)
# pass inputs with all kwargs in data
if parameters is not None:
prediction = self.pipeline(inputs, **parameters)
else:
prediction = self.pipeline(inputs)
# postprocess the prediction
return prediction
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