Convert dataset to Parquet

README.md

@@ -31,6 +31,206 @@ task_ids: []
 pretty_name: Samanantar
 tags:
 - conditional-text-generation
+dataset_info:
+- config_name: as
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 35548280
+    num_examples: 141227
+  download_size: 19404220
+  dataset_size: 35548280
+- config_name: bn
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 2204943013
+    num_examples: 8604580
+  download_size: 1197993546
+  dataset_size: 2204943013
+- config_name: gu
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 678219165
+    num_examples: 3067790
+  download_size: 370118693
+  dataset_size: 678219165
+- config_name: hi
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 3598130651
+    num_examples: 10125706
+  download_size: 1916386168
+  dataset_size: 3598130651
+- config_name: kn
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 908044345
+    num_examples: 4093524
+  download_size: 483451767
+  dataset_size: 908044345
+- config_name: ml
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1545010918
+    num_examples: 5924426
+  download_size: 784891308
+  dataset_size: 1545010918
+- config_name: mr
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 929465791
+    num_examples: 3627480
+  download_size: 487825355
+  dataset_size: 929465791
+- config_name: or
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 265698932
+    num_examples: 998228
+  download_size: 136203687
+  dataset_size: 265698932
+- config_name: pa
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 876144647
+    num_examples: 2980383
+  download_size: 470604570
+  dataset_size: 876144647
+- config_name: ta
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1518393368
+    num_examples: 5264867
+  download_size: 753886808
+  dataset_size: 1518393368
+- config_name: te
+  features:
+  - name: idx
+    dtype: int64
+  - name: src
+    dtype: string
+  - name: tgt
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1121643183
+    num_examples: 4946035
+  download_size: 599351284
+  dataset_size: 1121643183
+configs:
+- config_name: as
+  data_files:
+  - split: train
+    path: as/train-*
+- config_name: bn
+  data_files:
+  - split: train
+    path: bn/train-*
+- config_name: gu
+  data_files:
+  - split: train
+    path: gu/train-*
+- config_name: hi
+  data_files:
+  - split: train
+    path: hi/train-*
+- config_name: kn
+  data_files:
+  - split: train
+    path: kn/train-*
+- config_name: ml
+  data_files:
+  - split: train
+    path: ml/train-*
+- config_name: mr
+  data_files:
+  - split: train
+    path: mr/train-*
+- config_name: or
+  data_files:
+  - split: train
+    path: or/train-*
+- config_name: pa
+  data_files:
+  - split: train
+    path: pa/train-*
+- config_name: ta
+  data_files:
+  - split: train
+    path: ta/train-*
+- config_name: te
+  data_files:
+  - split: train
+    path: te/train-*
 ---
 
 # Dataset Card for Samanantar

as/train-00000-of-00001.parquet

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bn/train-00000-of-00005.parquet

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kn/train-00000-of-00002.parquet

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kn/train-00001-of-00002.parquet

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mr/train-00000-of-00002.parquet

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or/train-00000-of-00001.parquet

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pa/train-00000-of-00002.parquet

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pa/train-00001-of-00002.parquet

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samanantar.py

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-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""Samanantar dataset."""
-
-from pathlib import Path
-
-import datasets
-
-
-_CITATION = """\
-@misc{ramesh2021samanantar,
-      title={Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages},
-      author={Gowtham Ramesh and Sumanth Doddapaneni and Aravinth Bheemaraj and Mayank Jobanputra and Raghavan AK and Ajitesh Sharma and Sujit Sahoo and Harshita Diddee and Mahalakshmi J and Divyanshu Kakwani and Navneet Kumar and Aswin Pradeep and Srihari Nagaraj and Kumar Deepak and Vivek Raghavan and Anoop Kunchukuttan and Pratyush Kumar and Mitesh Shantadevi Khapra},
-      year={2021},
-      eprint={2104.05596},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}
-"""
-
-_DESCRIPTION = """\
-Samanantar is the largest publicly available parallel corpora collection for Indic languages: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu. The corpus has 49.6M sentence pairs between English to Indian Languages.
-"""
-
-_HOMEPAGE = "https://indicnlp.ai4bharat.org/samanantar/"
-
-_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International"
-
-_URLS = {
-    "0.3.0": "https://objectstore.e2enetworks.net/ai4b-public-nlu-nlg/samanantar_paper_version.zip",
-}
-_LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]
-
-
-class SamanantarConfig(datasets.BuilderConfig):
-    VERSION = datasets.Version("0.3.0")
-
-    def __init__(self, language=None, version=VERSION, **kwargs):
-        super().__init__(name=language, version=version, **kwargs)
-        self.language = language
-
-
-class Samanantar(datasets.GeneratorBasedBuilder):
-    """Samanantar dataset."""
-
-    BUILDER_CONFIG_CLASS = SamanantarConfig
-    BUILDER_CONFIGS = [SamanantarConfig(language=language) for language in _LANGUAGES]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "idx": datasets.Value("int64"),
-                    "src": datasets.Value("string"),
-                    "tgt": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS[str(self.config.version)]
-        data_dir = dl_manager.download_and_extract(urls)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_dir": (Path(data_dir) / "samanantar_paper_version" / f"en-{self.config.language}"),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, data_dir):
-        src_path = data_dir / "train.en"
-        tgt_path = data_dir / f"train.{self.config.language}"
-        with src_path.open(encoding="utf-8") as src_file, tgt_path.open(encoding="utf-8") as tgt_file:
-            for idx, (src_line, tgt_line) in enumerate(zip(src_file, tgt_file)):
-                yield idx, {"idx": idx, "src": src_line.strip(), "tgt": tgt_line.strip()}

ta/train-00000-of-00004.parquet

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