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from typing import Any, Dict, List
from transformers import Idefics2Processor, Idefics2Model
class EndpointHandler:
def __init__(self, path=""):
# Preload all the elements you are going to need at inference.
self.processor = Idefics2Processor.from_pretrained(path)
self.model = Idefics2Model.from_pretrained(path)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str` | `PIL.Image` | `np.array`)
kwargs
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
image = data.pop("inputs", data)
# process image
output = self.processor(images=image, return_tensors="pt")
generated_ids = self.model.generate(**output)
# run prediction
generated_text = self.processor.batch_decode(
generated_ids, skip_special_tokens=True
)
# decode output
print(generated_text)
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