mirror of
https://github.com/hiyouga/LlamaFactory.git
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72 lines
2.1 KiB
Python
72 lines
2.1 KiB
Python
# Copyright 2025 the LlamaFactory team.
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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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from typing import Callable, NotRequired, TypedDict
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from ...extras.types import Sample, SFTSample
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class AlpacaSample(TypedDict, total=False):
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system: NotRequired[str]
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instruction: NotRequired[str]
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input: NotRequired[str]
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output: NotRequired[str]
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def alpaca_converter(raw_sample: AlpacaSample) -> SFTSample:
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"""Convert Alpaca sample to SFT sample.
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Args:
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raw_sample (AlpacaSample): Alpaca sample.
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Returns:
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SFTSample: SFT sample.
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"""
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messages = []
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if "system" in raw_sample:
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messages.append(
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{"role": "system", "content": [{"type": "text", "value": raw_sample["system"]}], "loss_weight": 0.0}
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)
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if "instruction" in raw_sample or "input" in raw_sample:
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messages.append(
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{
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"role": "user",
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"content": [
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{"type": "text", "value": raw_sample.get("instruction", "") + raw_sample.get("input", "")}
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],
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"loss_weight": 0.0,
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}
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)
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if "output" in raw_sample:
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messages.append(
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{"role": "assistant", "content": [{"type": "text", "value": raw_sample["output"]}], "loss_weight": 1.0}
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)
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return {"messages": messages}
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CONVERTERS = {
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"alpaca": alpaca_converter,
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}
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def get_converter(converter_name: str) -> Callable[[dict], Sample]:
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if converter_name not in CONVERTERS:
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raise ValueError(f"Converter {converter_name} not found.")
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return CONVERTERS[converter_name]
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