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---
language:
- en
- uk
license: apache-2.0
dataset_info:
features:
- name: english
dtype: string
- name: ukrainian
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 130905422
num_examples: 286417
- name: validation
num_bytes: 899099
num_examples: 2000
- name: test
num_bytes: 902362
num_examples: 1898
- name: mono
num_bytes: 400416310
num_examples: 1461320
download_size: 278301105
dataset_size: 533123193
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
- split: mono
path: data/mono-*
---
## Dataset Downloader
This script allows you to download and save datasets from the Hugging Face Hub in the same format used for the experiments:
`python download_data.py --repo_name LT3/nfr_bt_nmt_english-ukrainian --base_path data/en-uk`
```
import argparse
from datasets import load_dataset
import os
def save_data(data, file_path):
with open(file_path, "w", encoding="utf-8") as f:
f.write("\n".join(data) + "\n")
def download_and_save_dataset(repo_name, base_path):
# Load the dataset from Hugging Face Hub
dataset = load_dataset(repo_name)
# Ensure the necessary directory exists
os.makedirs(base_path, exist_ok=True)
# Dictionary to store dataset paths
dataset_paths = {}
# Save the datasets to disk
for split in dataset.keys():
# Handle mono splits specially
if "mono_english" in split or "mono_ukrainian" in split or "mono_french" in split:
lang_code = "en" if "english" in split else ("uk" if "ukrainian" in split else "fr")
feature = "english" if "english" in split else ("ukrainian" if "ukrainian" in split else "french")
if feature in dataset[split].column_names:
path = f"{base_path}/{lang_code}_mono.txt"
save_data(dataset[split][feature], path)
dataset_paths[f"{lang_code}_mono"] = path
else:
# Save data for other splits
for feature in ["english", "french", "ukrainian"]:
if feature in dataset[split].column_names:
lang_code = "en" if feature == "english" else ("fr" if feature == "french" else "uk")
path = f"{base_path}/{lang_code}_{split}.txt"
save_data(dataset[split][feature], path)
dataset_paths[f"{lang_code}_{split}"] = path
print(dataset_paths)
def main():
parser = argparse.ArgumentParser(
description="Download and save datasets from Hugging Face."
)
parser.add_argument(
"--repo_name",
required=True,
help="Repository name on Hugging Face (e.g., 'MT-LT3/nfr_bt_nmt_english-french')",
)
parser.add_argument(
"--base_path",
required=True,
help="Base path where the dataset files will be saved (e.g., '/path/to/data/en-fr')",
)
args = parser.parse_args()
download_and_save_dataset(args.repo_name, args.base_path)
if __name__ == "__main__":
main()
``` |