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