Files
DataPipeline/scripts/supervised_finetuning/sft_magpie-pro-300k.py
T

25 lines
744 B
Python

from datasets import load_dataset
from pipeline import export_dataset
def process_func(input_dict: dict):
conversations = input_dict["conversations"]
assert len(conversations) % 2 == 0
n = len(conversations) // 2
examples = []
for i in range(n):
user_msg = conversations[2 * i]["value"]
assistant_msg = conversations[2 * i + 1]["value"]
examples.append({"query": user_msg, "response": assistant_msg})
return examples
if __name__ == "__main__":
dataset = load_dataset("HuggingFaceTB/Magpie-Pro-300K-Filtered-H4")
export_dataset(
dataset=dataset["train_sft"],
output_dir="./dataset",
output_prefix="Magpie-Pro-300K-sft",
process_func=process_func,
)