File size: 1,681 Bytes
0be1a5f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
#!/usr/bin/python3
# -*- coding: utf-8 -*-
"""
### convert to parquet
```text
参考:
https://huggingface.co/docs/datasets/main/en/cli#convert-to-parquet
在本地命令行输入 `huggingface-cli login` 后输入 token 登录.
$ huggingface-cli login
在本地命令行登录成功后执行:
datasets-cli convert_to_parquet intelli-zen/demand --trust_remote_code
执行完成后, 它会自动在 qgyd2021/demand 的 community 开启一个 duscussion.
You can find your PR to convert the dataset to Parquet at: https://huggingface.co/datasets/qgyd2021/demand/discussions/1
访问链接在下面找到 Merge, 点击将其合并. 之后, 很快 dataser viewer 就可以查看了.
```
"""
import argparse
from datasets import load_dataset
from project_settings import project_path
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--dataset_path",
default="demand.py",
# default="E:/Users/tianx/HuggingDatasets/demand/demand.py",
type=str
)
parser.add_argument("--dataset_name", default="kitchen_16k", type=str)
parser.add_argument(
"--dataset_cache_dir",
default=(project_path / "hub_datasets").as_posix(),
type=str
)
args = parser.parse_args()
return args
def main():
args = get_args()
dataset = load_dataset(
path=args.dataset_path,
name=args.dataset_name,
cache_dir=args.dataset_cache_dir,
# streaming=True,
trust_remote_code=True,
)
print(dataset.builder_configs)
for sample in dataset["train"]:
print(sample)
print("-" * 150)
return
if __name__ == '__main__':
main()
|