handler.py

from typing import  Dict, List, Any
from transformers import AutoModelForSeq2SeqLM, NllbTokenizerFast


class EndpointHandler():
    def __init__(self, path=""):
        # load the optimized model
        self.model = AutoModelForSeq2SeqLM.from_pretrained(path,load_in_4bit=True)
        self.tokenizer = NllbTokenizerFast.from_pretrained(path)

    def __call__(self, data: Dict[str,str]) -> Dict[str, str]:
        """
        Args:
            data (:obj:):
                includes the input data and the parameters for the inference.
        """
        text = data.get("text", data)
        langId = data.get("langId",data)

        # tokenize the input
        inputs = tokenizer(text, return_tensors="pt")
        # run the model
        translated_tokens = model.generate(**inputs, forced_bos_token_id=tokenizer.lang_code_to_id[langId], max_length=512)
        res = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)[0]
        # return
        return {"translated": res}