43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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# Copyright 2023 PKU-Alignment Team. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Stanford Alpaca dataset for supervised instruction fine-tuning."""
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from __future__ import annotations
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from datasets import load_dataset
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from .base import RawDataset, RawSample
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__all__ = ["AlpacaDataset"]
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class AlpacaDataset(RawDataset):
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NAME: str = "alpaca"
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ALIASES: tuple[str, ...] = ("stanford-alpaca",)
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def __init__(self, path: str | None = None) -> None:
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self.data = load_dataset(path or "tatsu-lab/alpaca", split="train")
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def __getitem__(self, index: int) -> RawSample:
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data = self.data[index]
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input = ( # pylint: disable=redefined-builtin
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" ".join((data["instruction"], data["input"])) if data["input"] else data["instruction"]
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)
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answer = data["output"]
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return RawSample(input=input, answer=answer)
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def __len__(self) -> int:
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return len(self.data)
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