)
        self.model = AutoModelForSequenceClassification.from_pretrained(
                    model_dir
                )
def preprocess(self, data):

    input_text = data.get("data")
    if input_text is None:
        input_text = data.get("body")
        inputs = self.tokenizer.encode_plus(input_text, max_length=int(max_length), pad_to_max_length=True, add_special_tokens=True, return_tensors='pt')
    return inputs

def inference(self,inputs):
    predictions = self.model(**inputs)
    return predictions

def postprocess(self, output):
    return output

```
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