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README (4).md

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+---
+annotations_creators:
+- no-annotation
+language_creators:
+- crowdsourced
+language:
+- en
+license:
+- cc-by-sa-3.0
+- gfdl
+multilinguality:
+- monolingual
+paperswithcode_id: wikitext-2
+pretty_name: WikiText
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- text-generation
+- fill-mask
+task_ids:
+- language-modeling
+- masked-language-modeling
+dataset_info:
+- config_name: wikitext-103-v1
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 1295579
+    num_examples: 4358
+  - name: train
+    num_bytes: 545142639
+    num_examples: 1801350
+  - name: validation
+    num_bytes: 1154755
+    num_examples: 3760
+  download_size: 190229076
+  dataset_size: 547592973
+- config_name: wikitext-2-v1
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 1270951
+    num_examples: 4358
+  - name: train
+    num_bytes: 10918134
+    num_examples: 36718
+  - name: validation
+    num_bytes: 1134127
+    num_examples: 3760
+  download_size: 4475746
+  dataset_size: 13323212
+- config_name: wikitext-103-raw-v1
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 1305092
+    num_examples: 4358
+  - name: train
+    num_bytes: 546501673
+    num_examples: 1801350
+  - name: validation
+    num_bytes: 1159292
+    num_examples: 3760
+  download_size: 191984949
+  dataset_size: 548966057
+- config_name: wikitext-2-raw-v1
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 1305092
+    num_examples: 4358
+  - name: train
+    num_bytes: 11061733
+    num_examples: 36718
+  - name: validation
+    num_bytes: 1159292
+    num_examples: 3760
+  download_size: 4721645
+  dataset_size: 13526117
+---
+
+# Dataset Card for "wikitext"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [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)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/](https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/)
+- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [Pointer Sentinel Mixture Models](https://arxiv.org/abs/1609.07843)
+- **Point of Contact:** [Stephen Merity](mailto:smerity@salesforce.com)
+- **Size of downloaded dataset files:** 391.41 MB
+- **Size of the generated dataset:** 1.12 GB
+- **Total amount of disk used:** 1.52 GB
+
+### Dataset Summary
+
+ The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified
+ Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike License.
+
+Compared to the preprocessed version of Penn Treebank (PTB), WikiText-2 is over 2 times larger and WikiText-103 is over
+110 times larger. The WikiText dataset also features a far larger vocabulary and retains the original case, punctuation
+and numbers - all of which are removed in PTB. As it is composed of full articles, the dataset is well suited for models
+that can take advantage of long term dependencies.
+
+Each subset comes in two different variants:
+- Raw (for character level work) contain the raw tokens, before the addition of the <unk> (unknown) tokens.
+- Non-raw (for word level work) contain only the tokens in their vocabulary (wiki.train.tokens, wiki.valid.tokens, and wiki.test.tokens).
+  The out-of-vocabulary tokens have been replaced with the the <unk> token.
+
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Languages
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Dataset Structure
+
+### Data Instances
+
+#### wikitext-103-raw-v1
+
+- **Size of downloaded dataset files:** 191.98 MB
+- **Size of the generated dataset:** 549.42 MB
+- **Total amount of disk used:** 741.41 MB
+
+An example of 'validation' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    "text": "\" The gold dollar or gold one @-@ dollar piece was a coin struck as a regular issue by the United States Bureau of the Mint from..."
+}
+```
+
+#### wikitext-103-v1
+
+- **Size of downloaded dataset files:** 190.23 MB
+- **Size of the generated dataset:** 548.05 MB
+- **Total amount of disk used:** 738.27 MB
+
+An example of 'train' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    "text": "\" Senjō no Valkyria 3 : <unk> Chronicles ( Japanese : 戦場のヴァルキュリア3 , lit . Valkyria of the Battlefield 3 ) , commonly referred to..."
+}
+```
+
+#### wikitext-2-raw-v1
+
+- **Size of downloaded dataset files:** 4.72 MB
+- **Size of the generated dataset:** 13.54 MB
+- **Total amount of disk used:** 18.26 MB
+
+An example of 'train' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    "text": "\" The Sinclair Scientific Programmable was introduced in 1975 , with the same case as the Sinclair Oxford . It was larger than t..."
+}
+```
+
+#### wikitext-2-v1
+
+- **Size of downloaded dataset files:** 4.48 MB
+- **Size of the generated dataset:** 13.34 MB
+- **Total amount of disk used:** 17.82 MB
+
+An example of 'train' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    "text": "\" Senjō no Valkyria 3 : <unk> Chronicles ( Japanese : 戦場のヴァルキュリア3 , lit . Valkyria of the Battlefield 3 ) , commonly referred to..."
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### wikitext-103-raw-v1
+- `text`: a `string` feature.
+
+#### wikitext-103-v1
+- `text`: a `string` feature.
+
+#### wikitext-2-raw-v1
+- `text`: a `string` feature.
+
+#### wikitext-2-v1
+- `text`: a `string` feature.
+
+### Data Splits
+
+|       name        | train |validation|test|
+|-------------------|------:|---------:|---:|
+|wikitext-103-raw-v1|1801350|      3760|4358|
+|wikitext-103-v1    |1801350|      3760|4358|
+|wikitext-2-raw-v1  |  36718|      3760|4358|
+|wikitext-2-v1      |  36718|      3760|4358|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the source language producers?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the annotators?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Personal and Sensitive Information
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Discussion of Biases
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Other Known Limitations
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Licensing Information
+
+The dataset is available under the [Creative Commons Attribution-ShareAlike License (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/).
+
+### Citation Information
+
+```
+@misc{merity2016pointer,
+      title={Pointer Sentinel Mixture Models},
+      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},
+      year={2016},
+      eprint={1609.07843},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+
+### Contributions
+
+Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten), [@mariamabarham](https://github.com/mariamabarham) for adding this dataset.

dataset_infos.json

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+{"wikitext-103-v1": {"description": " The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified\n Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike\n License.\n", "citation": "@misc{merity2016pointer,\n      title={Pointer Sentinel Mixture Models},\n      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},\n      year={2016},\n      eprint={1609.07843},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/", "license": "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wikitext", "config_name": "wikitext-103-v1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1295579, "num_examples": 4358, "dataset_name": "wikitext"}, "train": {"name": "train", "num_bytes": 545142639, "num_examples": 1801350, "dataset_name": "wikitext"}, "validation": {"name": "validation", "num_bytes": 1154755, "num_examples": 3760, "dataset_name": "wikitext"}}, "download_checksums": {"https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-103-v1.zip": {"num_bytes": 190229076, "checksum": "242ba0f20b329cfdf1ccc61e9e9e5b59becf189db7f7a81cd2a0e2fc31539590"}}, "download_size": 190229076, "post_processing_size": null, "dataset_size": 547592973, "size_in_bytes": 737822049}, "wikitext-2-v1": {"description": " The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified\n Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike\n License.\n", "citation": "@misc{merity2016pointer,\n      title={Pointer Sentinel Mixture Models},\n      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},\n      year={2016},\n      eprint={1609.07843},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/", "license": "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wikitext", "config_name": "wikitext-2-v1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1270951, "num_examples": 4358, "dataset_name": "wikitext"}, "train": {"name": "train", "num_bytes": 10918134, "num_examples": 36718, "dataset_name": "wikitext"}, "validation": {"name": "validation", "num_bytes": 1134127, "num_examples": 3760, "dataset_name": "wikitext"}}, "download_checksums": {"https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-v1.zip": {"num_bytes": 4475746, "checksum": "92675f1d63015c1c8b51f1656a52d5bdbc33aafa60cc47a218a66e7ee817488c"}}, "download_size": 4475746, "post_processing_size": null, "dataset_size": 13323212, "size_in_bytes": 17798958}, "wikitext-103-raw-v1": {"description": " The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified\n Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike\n License.\n", "citation": "@misc{merity2016pointer,\n      title={Pointer Sentinel Mixture Models},\n      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},\n      year={2016},\n      eprint={1609.07843},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/", "license": "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wikitext", "config_name": "wikitext-103-raw-v1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1305092, "num_examples": 4358, "dataset_name": "wikitext"}, "train": {"name": "train", "num_bytes": 546501673, "num_examples": 1801350, "dataset_name": "wikitext"}, "validation": {"name": "validation", "num_bytes": 1159292, "num_examples": 3760, "dataset_name": "wikitext"}}, "download_checksums": {"https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-103-raw-v1.zip": {"num_bytes": 191984949, "checksum": "91c00ae287f0d699e18605c84afc9e45c192bc6b7797ff8837e5474655a33794"}}, "download_size": 191984949, "post_processing_size": null, "dataset_size": 548966057, "size_in_bytes": 740951006}, "wikitext-2-raw-v1": {"description": " The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified\n Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike\n License.\n", "citation": "@misc{merity2016pointer,\n      title={Pointer Sentinel Mixture Models},\n      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},\n      year={2016},\n      eprint={1609.07843},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/", "license": "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "wikitext", "config_name": "wikitext-2-raw-v1", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 1305092, "num_examples": 4358, "dataset_name": "wikitext"}, "train": {"name": "train", "num_bytes": 11061733, "num_examples": 36718, "dataset_name": "wikitext"}, "validation": {"name": "validation", "num_bytes": 1159292, "num_examples": 3760, "dataset_name": "wikitext"}}, "download_checksums": {"https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip": {"num_bytes": 4721645, "checksum": "ef7edb566e3e2b2d31b29c1fdb0c89a4cc683597484c3dc2517919c615435a11"}}, "download_size": 4721645, "post_processing_size": null, "dataset_size": 13526117, "size_in_bytes": 18247762}}

wikitext.py

@@ -0,0 +1,192 @@
+"""TODO(wikitext): Add a description here."""
+
+
+import os
+
+import datasets
+
+
+_CITATION = """\
+@misc{merity2016pointer,
+      title={Pointer Sentinel Mixture Models},
+      author={Stephen Merity and Caiming Xiong and James Bradbury and Richard Socher},
+      year={2016},
+      eprint={1609.07843},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+ The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified
+ Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike
+ License.
+"""
+_HOMEPAGE = "https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/"
+_LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)"
+_DATA_URL = "https://s3.amazonaws.com/research.metamind.io/wikitext"
+
+
+class WikitextConfig(datasets.BuilderConfig):
+    """BuilderConfig for GLUE."""
+
+    def __init__(self, data_url, **kwargs):
+        """BuilderConfig for Wikitext
+
+        Args:
+          data_url: `string`, url to the dataset (word or raw level)
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(WikitextConfig, self).__init__(
+            version=datasets.Version(
+                "1.0.0",
+            ),
+            **kwargs,
+        )
+        self.data_url = data_url
+
+
+class Wikitext(datasets.GeneratorBasedBuilder):
+    """TODO(wikitext_103): Short description of my dataset."""
+
+    # TODO(wikitext_103): Set up version.
+    VERSION = datasets.Version("0.1.0")
+    BUILDER_CONFIGS = [
+        WikitextConfig(
+            name="wikitext-103-v1",
+            data_url=_DATA_URL + "/" + "wikitext-103-v1.zip",
+            description="Word level dataset. No processing is needed other than replacing newlines with <eos> tokens.",
+        ),
+        WikitextConfig(
+            name="wikitext-2-v1",
+            data_url=_DATA_URL + "/" + "wikitext-2-v1.zip",
+            description="Word level dataset. No processing is needed other than replacing newlines with <eos> tokens.",
+        ),
+        WikitextConfig(
+            name="wikitext-103-raw-v1",
+            data_url=_DATA_URL + "/" + "wikitext-103-raw-v1.zip",
+            description="Raw level dataset: the raw tokens before the addition of <unk> tokens. "
+            "They should only be used for character level work or for creating newly derived datasets.",
+        ),
+        WikitextConfig(
+            name="wikitext-2-raw-v1",
+            data_url=_DATA_URL + "/" + "wikitext-2-raw-v1.zip",
+            description="Raw level dataset: the raw tokens before the addition of <unk> tokens. "
+            "They should only be used for character level work or for creating newly derived datasets.",
+        ),
+    ]
+
+    def _info(self):
+        # TODO(wikitext): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(wikitext): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        if self.config.name == "wikitext-103-v1":
+            data_file = dl_manager.download_and_extract(self.config.data_url)
+            data_dir = os.path.join(data_file, "wikitext-103")
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    gen_kwargs={"data_file": os.path.join(data_dir, "wiki.test.tokens"), "split": "test"},
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={"data_file": os.path.join(data_dir, "wiki.train.tokens"), "split": "train"},
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    gen_kwargs={"data_file": os.path.join(data_dir, "wiki.valid.tokens"), "split": "valid"},
+                ),
+            ]
+        else:
+            if self.config.name == "wikitext-103-raw-v1":
+                data_file = dl_manager.download_and_extract(self.config.data_url)
+                data_dir = os.path.join(data_file, "wikitext-103-raw")
+                return [
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TEST,
+                        gen_kwargs={"data_file": os.path.join(data_dir, "wiki.test.raw"), "split": "test"},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TRAIN,
+                        gen_kwargs={"data_file": os.path.join(data_dir, "wiki.train.raw"), "split": "train"},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.VALIDATION,
+                        gen_kwargs={"data_file": os.path.join(data_dir, "wiki.valid.raw"), "split": "valid"},
+                    ),
+                ]
+            else:
+                if self.config.name == "wikitext-2-raw-v1":
+                    data_file = dl_manager.download_and_extract(self.config.data_url)
+                    data_dir = os.path.join(data_file, "wikitext-2-raw")
+                    return [
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TEST,
+                            gen_kwargs={"data_file": os.path.join(data_dir, "wiki.test.raw"), "split": "test"},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TRAIN,
+                            gen_kwargs={"data_file": os.path.join(data_dir, "wiki.train.raw"), "split": "train"},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.VALIDATION,
+                            gen_kwargs={"data_file": os.path.join(data_dir, "wiki.valid.raw"), "split": "valid"},
+                        ),
+                    ]
+                else:
+                    if self.config.name == "wikitext-2-v1":
+                        data_file = dl_manager.download_and_extract(self.config.data_url)
+                        data_dir = os.path.join(data_file, "wikitext-2")
+                        return [
+                            datasets.SplitGenerator(
+                                name=datasets.Split.TEST,
+                                gen_kwargs={"data_file": os.path.join(data_dir, "wiki.test.tokens"), "split": "test"},
+                            ),
+                            datasets.SplitGenerator(
+                                name=datasets.Split.TRAIN,
+                                gen_kwargs={
+                                    "data_file": os.path.join(data_dir, "wiki.train.tokens"),
+                                    "split": "train",
+                                },
+                            ),
+                            datasets.SplitGenerator(
+                                name=datasets.Split.VALIDATION,
+                                gen_kwargs={
+                                    "data_file": os.path.join(data_dir, "wiki.valid.tokens"),
+                                    "split": "valid",
+                                },
+                            ),
+                        ]
+
+    def _generate_examples(self, data_file, split):
+
+        """Yields examples."""
+        # TODO(wikitext): Yields (key, example) tuples from the dataset
+        with open(data_file, encoding="utf-8") as f:
+            for idx, row in enumerate(f):
+                if row.strip():
+                    yield idx, {"text": row}
+                else:
+                    yield idx, {"text": ""}