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| | import pytest |
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| | from llamafactory.data import Role |
| | from llamafactory.data.converter import get_dataset_converter |
| | from llamafactory.data.parser import DatasetAttr |
| | from llamafactory.hparams import DataArguments |
| |
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|
| | @pytest.mark.runs_on(["cpu", "mps"]) |
| | def test_alpaca_converter(): |
| | dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset") |
| | data_args = DataArguments() |
| | example = { |
| | "instruction": "Solve the math problem.", |
| | "input": "3 + 4", |
| | "output": "The answer is 7.", |
| | } |
| | dataset_converter = get_dataset_converter("alpaca", dataset_attr, data_args) |
| | assert dataset_converter(example) == { |
| | "_prompt": [{"role": Role.USER.value, "content": "Solve the math problem.\n3 + 4"}], |
| | "_response": [{"role": Role.ASSISTANT.value, "content": "The answer is 7."}], |
| | "_system": "", |
| | "_tools": "", |
| | "_images": None, |
| | "_videos": None, |
| | "_audios": None, |
| | } |
| |
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|
| | @pytest.mark.runs_on(["cpu", "mps"]) |
| | def test_sharegpt_converter(): |
| | dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset") |
| | data_args = DataArguments() |
| | example = { |
| | "conversations": [ |
| | {"from": "system", "value": "You are a helpful assistant."}, |
| | {"from": "human", "value": "Solve the math problem.\n3 + 4"}, |
| | {"from": "gpt", "value": "The answer is 7."}, |
| | ] |
| | } |
| | dataset_converter = get_dataset_converter("sharegpt", dataset_attr, data_args) |
| | assert dataset_converter(example) == { |
| | "_prompt": [{"role": Role.USER.value, "content": "Solve the math problem.\n3 + 4"}], |
| | "_response": [{"role": Role.ASSISTANT.value, "content": "The answer is 7."}], |
| | "_system": "You are a helpful assistant.", |
| | "_tools": "", |
| | "_images": None, |
| | "_videos": None, |
| | "_audios": None, |
| | } |
| |
|