Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.bin.* filter=lfs diff=lfs merge=lfs -text
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+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- en
+licenses:
+- cc-by-sa-3-0
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- table-to-text
+---
+
+# Dataset Card Creation Guide
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** None
+- **Repository:** https://github.com/google-research-datasets/ToTTo
+- **Paper:** https://arxiv.org/abs/2004.14373
+- **Leaderboard:** https://github.com/google-research-datasets/ToTTo#leaderboard
+- **Point of Contact:** totto@google.com
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+```
+DatasetDict({
+    train: Dataset({
+        features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
+        num_rows: 120761
+    })
+    validation: Dataset({
+        features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
+        num_rows: 7700
+    })
+    test: Dataset({
+        features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],
+        num_rows: 7700
+    })
+})
+```
+
+### Data Fields
+
+A sample training set is provided below
+
+```
+{'example_id': '1762238357686640028',
+ 'highlighted_cells': [[13, 2]],
+ 'id': 0,
+ 'overlap_subset': 'none',
+ 'sentence_annotations': {'final_sentence': ['A Favorita is the telenovela aired in the 9 pm timeslot.'],
+  'original_sentence': ['It is also the first telenovela by the writer to air in the 9 pm timeslot.'],
+  'sentence_after_ambiguity': ['A Favorita is the telenovela aired in the 9 pm timeslot.'],
+  'sentence_after_deletion': ['It is the telenovela air in the 9 pm timeslot.']},
+ 'table': [[{'column_span': 1, 'is_header': True, 'row_span': 1, 'value': '#'},
+   {'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Run'},
+   {'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Title'},
+   {'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Chapters'},
+   {'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Author'},
+   {'column_span': 1, 'is_header': True, 'row_span': 1, 'value': 'Director'},
+   {'column_span': 1,
+    'is_header': True,
+    'row_span': 1,
+    'value': 'Ibope Rating'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '59'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'June 5, 2000— February 2, 2001'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Laços de Família'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Manoel Carlos'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Ricardo Waddington'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '44.9'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '60'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'February 5, 2001— September 28, 2001'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Porto dos Milagres'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Aguinaldo Silva Ricardo Linhares'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Marcos Paulo Simões'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '44.6'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '61'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'October 1, 2001— June 14, 2002'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'O Clone'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Glória Perez'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Jayme Monjardim'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '47.0'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '62'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'June 17, 2002— February 14, 2003'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Esperança'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Benedito Ruy Barbosa'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Luiz Fernando'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '37.7'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '63'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'February 17, 2003— October 10, 2003'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Mulheres Apaixonadas'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Manoel Carlos'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Ricardo Waddington'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.6'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '64'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'October 13, 2003— June 25, 2004'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Celebridade'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Gilberto Braga'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Dennis Carvalho'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.0'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '65'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'June 28, 2004— March 11, 2005'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Senhora do Destino'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '221'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Aguinaldo Silva'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Wolf Maya'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '50.4'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '66'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'March 14, 2005— November 4, 2005'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'América'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Glória Perez'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Jayme Monjardim Marcos Schechtman'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '49.4'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '67'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'November 7, 2005— July 7, 2006'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Belíssima'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Sílvio de Abreu'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Denise Saraceni'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '48.5'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '68'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'July 10, 2006— March 2, 2007'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Páginas da Vida'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Manoel Carlos'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Jayme Monjardim'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '46.8'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '69'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'March 5, 2007— September 28, 2007'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Paraíso Tropical'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '179'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Gilberto Braga Ricardo Linhares'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Dennis Carvalho'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '42.8'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '70'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'October 1, 2007— May 31, 2008'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Duas Caras'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '210'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Aguinaldo Silva'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': 'Wolf Maya'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '41.1'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '71'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'June 2, 2008— January 16, 2009'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'A Favorita'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '197'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'João Emanuel Carneiro'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Ricardo Waddington'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '39.5'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '72'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'January 19, 2009— September 11, 2009'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Caminho das Índias'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '203'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Glória Perez'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Marcos Schechtman'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '38.8'}],
+  [{'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '73'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'September 14, 2009— May 14, 2010'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Viver a Vida'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '209'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Manoel Carlos'},
+   {'column_span': 1,
+    'is_header': False,
+    'row_span': 1,
+    'value': 'Jayme Monjardim'},
+   {'column_span': 1, 'is_header': False, 'row_span': 1, 'value': '35.6'}]],
+ 'table_page_title': 'List of 8/9 PM telenovelas of Rede Globo',
+ 'table_section_text': '',
+ 'table_section_title': '2000s',
+ 'table_webpage_url': 'http://en.wikipedia.org/wiki/List_of_8/9_PM_telenovelas_of_Rede_Globo'}
+```
+
+Please note that in test set sentence annotations are not available and thus values inside `sentence_annotations` can be safely ignored.
+
+### Data Splits
+
+[More Information Needed]
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.\n", "citation": "@inproceedings{parikh2020totto,\n  title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},\n  author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},\n  booktitle={Proceedings of EMNLP},\n  year={2020}\n }\n", "homepage": "", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "table_page_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_webpage_url": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_title": {"dtype": "string", "id": null, "_type": "Value"}, "table_section_text": {"dtype": "string", "id": null, "_type": "Value"}, "table": [[{"column_span": {"dtype": "int32", "id": null, "_type": "Value"}, "is_header": {"dtype": "bool", "id": null, "_type": "Value"}, "row_span": {"dtype": "int32", "id": null, "_type": "Value"}, "value": {"dtype": "string", "id": null, "_type": "Value"}}]], "highlighted_cells": {"feature": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "example_id": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_annotations": {"feature": {"original_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_deletion": {"dtype": "string", "id": null, "_type": "Value"}, "sentence_after_ambiguity": {"dtype": "string", "id": null, "_type": "Value"}, "final_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "overlap_subset": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "totto", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 652754806, "num_examples": 120761, "dataset_name": "totto"}, "validation": {"name": "validation", "num_bytes": 47277039, "num_examples": 7700, "dataset_name": "totto"}, "test": {"name": "test", "num_bytes": 40883586, "num_examples": 7700, "dataset_name": "totto"}}, "download_checksums": {"https://storage.googleapis.com/totto/totto_data.zip": {"num_bytes": 187724372, "checksum": "0aab72597057394514fd9659745fd2b318d1a64bf0b2ca1b2c339abe0692fdf2"}}, "download_size": 187724372, "post_processing_size": null, "dataset_size": 740915431, "size_in_bytes": 928639803}}

dummy/1.0.0/dummy_data.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b57038271f6118f6e6106658f421890a344a9cf28b633a9ad14f1d46eac6ccad
+size 24427

totto.py

@@ -0,0 +1,137 @@
+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+import json
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
+"""
+_HOMEPAGE_URL = ""
+_URL = "https://storage.googleapis.com/totto/totto_data.zip"
+_CITATION = """\
+@inproceedings{parikh2020totto,
+  title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
+  author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
+  booktitle={Proceedings of EMNLP},
+  year={2020}
+ }
+"""
+
+
+class Totto(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "table_page_title": datasets.Value("string"),
+                    "table_webpage_url": datasets.Value("string"),
+                    "table_section_title": datasets.Value("string"),
+                    "table_section_text": datasets.Value("string"),
+                    "table": [
+                        [
+                            {
+                                "column_span": datasets.Value("int32"),
+                                "is_header": datasets.Value("bool"),
+                                "row_span": datasets.Value("int32"),
+                                "value": datasets.Value("string"),
+                            }
+                        ]
+                    ],
+                    "highlighted_cells": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
+                    "example_id": datasets.Value("string"),
+                    "sentence_annotations": datasets.Sequence(
+                        {
+                            "original_sentence": datasets.Value("string"),
+                            "sentence_after_deletion": datasets.Value("string"),
+                            "sentence_after_ambiguity": datasets.Value("string"),
+                            "final_sentence": datasets.Value("string"),
+                        }
+                    ),
+                    "overlap_subset": datasets.Value("string"),
+                },
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        path = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "datapath": os.path.join(path, "totto_data/totto_train_data.jsonl"),
+                    "datatype": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "datapath": os.path.join(path, "totto_data/totto_dev_data.jsonl"),
+                    "datatype": "valid",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "datapath": os.path.join(path, "totto_data/unlabeled_totto_test_data.jsonl"),
+                    "datatype": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, datapath, datatype):
+        with open(datapath, "r", encoding="utf-8") as json_file:
+            json_list = list(json_file)
+
+        for example_counter, json_str in enumerate(json_list):
+            result = json.loads(json_str)
+            response = {
+                "id": example_counter,
+                "table_page_title": result["table_page_title"],
+                "table_webpage_url": result["table_webpage_url"],
+                "table_section_title": result["table_section_title"],
+                "table_section_text": result["table_section_text"],
+                "table": result["table"],
+                "highlighted_cells": result["highlighted_cells"],
+                "example_id": str(result["example_id"]),
+            }
+            if datatype == "train":
+                response["overlap_subset"] = "none"
+            else:
+                response["overlap_subset"] = str(result["overlap_subset"])
+
+            if datatype == "test":
+                response["sentence_annotations"] = [
+                    {
+                        "original_sentence": "none",
+                        "sentence_after_deletion": "none",
+                        "sentence_after_ambiguity": "none",
+                        "final_sentence": "none",
+                    }
+                ]
+            else:
+                response["sentence_annotations"] = result["sentence_annotations"]
+            yield example_counter, response