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from typing import Dict, List, Any |
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from transformers import pipeline, AutoTokenizer, BartForConditionalGeneration |
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class EndpointHandler(): |
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def __init__(self, path=""): |
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self.model = BartForConditionalGeneration.from_pretrained(path) |
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self.tokenizer = AutoTokenizer(path) |
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def __call__(self, data: str) -> str: |
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""" |
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data args: |
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inputs (:obj: `str`) |
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date (:obj: `str`) |
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Return: |
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A :obj:`list` | `dict`: will be serialized and returned |
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""" |
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text_tokenized = self.tokenizer( |
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[data], padding="max_length", truncation=True, max_length=1024,return_tensors='pt') |
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prediction_token = self.model.generate(text_tokenized["input_ids"], max_length = 256, num_beams = 6) |
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prediction_summary = self.tokenizer.decode(prediction_token[0][2:-1:1]) |
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return prediction_summary |
