refactor(dataset): 重构数据集处理逻辑

This commit is contained in:
2025-07-14 08:45:01 +08:00
parent d4df706bc5
commit 7591a231df
4 changed files with 57 additions and 80 deletions
+5 -26
View File
@@ -1,28 +1,7 @@
from datasets import load_dataset
import json
import os
from utils import process_dataset
if __name__ == "__main__":
dataset_dict = load_dataset("shjwudp/chinese-c4")
train_dataset = dataset_dict["train"]
chunk_size = 1000000
total_samples = len(train_dataset)
num_chunks = (total_samples // chunk_size) + 1
script_dir = os.path.dirname(os.path.abspath(__file__))
output_dir = os.path(script_dir, "dataset", "chinese-c4")
os.makedirs(output_dir, exist_ok=True)
for i in range(num_chunks):
start_idx = i * chunk_size
end_idx = min((i + 1) * chunk_size, total_samples)
chunk = train_dataset.select(range(start_idx, end_idx))
output_path = f"{output_dir}/chinese-c4_text_chunk_{i}.jsonl"
with open(output_path, "w", encoding="utf-8") as f:
for example in chunk:
# 每行写入一个 {"text": "xxx"} 对象
json_line = {"text": example["text"]}
f.write(json.dumps(json_line, ensure_ascii=False) + "\n")
print(f"Saved text chunk {i} to {output_path}")
process_dataset(
dataset_name="shjwudp/chinese-c4",
output_subdir="chinese-c4"
)