Update link in wiki_bio dataset (#3651)

* update link in wiki_bio dataset

* run linter and update dummy data

* fix markdown so that test passes (even though I didnt break it)

Commit from https://github.com/huggingface/datasets/commit/ffc35f41b41d6be6e067934b680f7abda2e91d49

README.md

@@ -52,7 +52,7 @@ pretty_name: WikiBio
 
 - **Repository:** https://github.com/DavidGrangier/wikipedia-biography-dataset
 - **Paper:** https://arxiv.org/pdf/1603.07771.pdf
-- **GoogleDrive:** https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil
+- **GitHub:** https://github.com/DavidGrangier/wikipedia-biography-dataset
 
 ### Dataset Summary
 
@@ -69,7 +69,7 @@ English.
 
 ### Data Instances
 
-[More Information Needed]
+More Information Needed
 
 ### Data Fields
 
@@ -132,7 +132,7 @@ where, in the `"table"` field, all the information of the Wikpedia infobox is st
 [More Information Needed]
 
 ### Source Data
-This dataset was announced in the paper <em>Neural Text Generation from Structured Data with Application to the Biography Domain</em> [(arxiv link)](https://arxiv.org/pdf/1603.07771.pdf) and is stored both in [this](https://github.com/DavidGrangier/wikipedia-biography-dataset) repo (owned by DavidGrangier) and in [Google Drive](https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil) (zipped and mantained by the TensorFlow team).
+This dataset was announced in the paper <em>Neural Text Generation from Structured Data with Application to the Biography Domain</em> [(arxiv link)](https://arxiv.org/pdf/1603.07771.pdf) and is stored in [this](https://github.com/DavidGrangier/wikipedia-biography-dataset) repo (owned by DavidGrangier).
 #### Initial Data Collection and Normalization
 
 [More Information Needed]

dataset_infos.json

@@ -1 +1 @@
-{"default": {"description": "This dataset gathers 728,321 biographies from wikipedia. It aims at evaluating text generation\nalgorithms. For each article, we provide the first paragraph and the infobox (both tokenized).\nFor each article, we extracted the first paragraph (text), the infobox (structured data). Each\ninfobox is encoded as a list of (field name, field value) pairs. We used Stanford CoreNLP\n(http://stanfordnlp.github.io/CoreNLP/) to preprocess the data, i.e. we broke the text into\nsentences and tokenized both the text and the field values. The dataset was randomly split in\nthree subsets train (80%), valid (10%), test (10%).\n", "citation": "@article{DBLP:journals/corr/LebretGA16,\n  author    = {R{'{e}}mi Lebret and\n               David Grangier and\n               Michael Auli},\n  title     = {Generating Text from Structured Data with Application to the Biography\n               Domain},\n  journal   = {CoRR},\n  volume    = {abs/1603.07771},\n  year      = {2016},\n  url       = {http://arxiv.org/abs/1603.07771},\n  archivePrefix = {arXiv},\n  eprint    = {1603.07771},\n  timestamp = {Mon, 13 Aug 2018 16:48:30 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/LebretGA16.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/DavidGrangier/wikipedia-biography-dataset", "license": "CC BY-SA 3.0", "features": {"input_text": {"table": {"feature": {"column_header": {"dtype": "string", "id": null, "_type": "Value"}, "row_number": {"dtype": "int16", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "context": {"dtype": "string", "id": null, "_type": "Value"}}, "target_text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "input_text", "output": "target_text"}, "builder_name": "wiki_bio", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 618362475, "num_examples": 582659, "dataset_name": "wiki_bio"}, "test": {"name": "test", "num_bytes": 77151324, "num_examples": 72831, "dataset_name": "wiki_bio"}, "val": {"name": "val", "num_bytes": 77221530, "num_examples": 72831, "dataset_name": "wiki_bio"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil": {"num_bytes": 333998704, "checksum": "0de0fef4cc6c9182138939134b81b6ac33ffbc989b6d23a2d9ef1e50c49b8032"}}, "download_size": 333998704, "post_processing_size": null, "dataset_size": 772735329, "size_in_bytes": 1106734033}}
+{"default": {"description": "This dataset gathers 728,321 biographies from wikipedia. It aims at evaluating text generation\nalgorithms. For each article, we provide the first paragraph and the infobox (both tokenized).\nFor each article, we extracted the first paragraph (text), the infobox (structured data). Each\ninfobox is encoded as a list of (field name, field value) pairs. We used Stanford CoreNLP\n(http://stanfordnlp.github.io/CoreNLP/) to preprocess the data, i.e. we broke the text into\nsentences and tokenized both the text and the field values. The dataset was randomly split in\nthree subsets train (80%), valid (10%), test (10%).\n", "citation": "@article{DBLP:journals/corr/LebretGA16,\n  author    = {R{'{e}}mi Lebret and\n               David Grangier and\n               Michael Auli},\n  title     = {Generating Text from Structured Data with Application to the Biography\n               Domain},\n  journal   = {CoRR},\n  volume    = {abs/1603.07771},\n  year      = {2016},\n  url       = {http://arxiv.org/abs/1603.07771},\n  archivePrefix = {arXiv},\n  eprint    = {1603.07771},\n  timestamp = {Mon, 13 Aug 2018 16:48:30 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/LebretGA16.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/DavidGrangier/wikipedia-biography-dataset", "license": "CC BY-SA 3.0", "features": {"input_text": {"table": {"feature": {"column_header": {"dtype": "string", "id": null, "_type": "Value"}, "row_number": {"dtype": "int16", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "context": {"dtype": "string", "id": null, "_type": "Value"}}, "target_text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "input_text", "output": "target_text"}, "task_templates": null, "builder_name": "wiki_bio", "config_name": "default", "version": {"version_str": "1.2.0", "description": null, "major": 1, "minor": 2, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 619269257, "num_examples": 582659, "dataset_name": "wiki_bio"}, "test": {"name": "test", "num_bytes": 77264695, "num_examples": 72831, "dataset_name": "wiki_bio"}, "val": {"name": "val", "num_bytes": 77335069, "num_examples": 72831, "dataset_name": "wiki_bio"}}, "download_checksums": {"https://huggingface.co/datasets/wiki_bio/resolve/main/data/wikipedia-biography-dataset.zip": {"num_bytes": 333998704, "checksum": "0de0fef4cc6c9182138939134b81b6ac33ffbc989b6d23a2d9ef1e50c49b8032"}}, "download_size": 333998704, "post_processing_size": null, "dataset_size": 773869021, "size_in_bytes": 1107867725}}

wiki_bio.py

@@ -56,9 +56,7 @@ _HOMEPAGE = "https://github.com/DavidGrangier/wikipedia-biography-dataset"
 
 _LICENSE = "CC BY-SA 3.0"
 
-# The HuggingFace dataset library don't host the datasets but only point to the original files
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://drive.google.com/uc?export=download&id=1L7aoUXzHPzyzQ0ns4ApBbYepsjFOtXil"
+_URL = "https://huggingface.co/datasets/wiki_bio/resolve/main/data/wikipedia-biography-dataset.zip"
 
 
 def _get_table(infobox_line):
@@ -92,7 +90,7 @@ def _get_table(infobox_line):
 class WikiBio(datasets.GeneratorBasedBuilder):
     """Infoboxes and first paragraph from Wikipedia biography pages."""
 
-    VERSION = datasets.Version("1.1.0")
+    VERSION = datasets.Version("1.2.0")
 
     def _info(self):
         features = datasets.Features(
@@ -121,8 +119,7 @@ class WikiBio(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        my_urls = _URL
-        data_dir = dl_manager.download_and_extract(my_urls)
+        data_dir = dl_manager.download_and_extract(_URL)
         data_path = os.path.join(data_dir, "wikipedia-biography-dataset")
         return [
             datasets.SplitGenerator(