Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -1,15 +1,14 @@
 ---
 annotations_creators:
 - crowdsourced
-language:
-- en
 language_creators:
 - found
+language:
+- en
 license:
 - other
 multilinguality:
 - monolingual
-pretty_name: 'CoQA: Conversational Question Answering Challenge'
 size_categories:
 - 1K<n<10K
 source_datasets:
@@ -22,6 +21,7 @@ task_categories:
 task_ids:
 - extractive-qa
 paperswithcode_id: coqa
+pretty_name: 'CoQA: Conversational Question Answering Challenge'
 tags:
 - conversational-qa
 dataset_info:
@@ -42,13 +42,20 @@ dataset_info:
       dtype: int32
   splits:
   - name: train
-    num_bytes: 17981459
+    num_bytes: 17953365
     num_examples: 7199
   - name: validation
-    num_bytes: 1225518
+    num_bytes: 1223427
     num_examples: 500
-  download_size: 58092681
-  dataset_size: 19206977
+  download_size: 12187487
+  dataset_size: 19176792
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
 ---
 
 # Dataset Card for "coqa"

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4272ee344ef27112c50237a1ae3b1c90e65e11a101d6874b2f57e4c08d147135
+size 11394343

data/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d66f4811dd137818923a3db7a629ce3cf9e73977b5e2541471311c1566bf349f
+size 793144

dataset_infos.json

@@ -1 +1,68 @@
-{"default": {"description": "CoQA: A Conversational Question Answering Challenge\n", "citation": "@article{reddy-etal-2019-coqa,\n    title = \"{C}o{QA}: A Conversational Question Answering Challenge\",\n    author = \"Reddy, Siva  and\n      Chen, Danqi  and\n      Manning, Christopher D.\",\n    journal = \"Transactions of the Association for Computational Linguistics\",\n    volume = \"7\",\n    year = \"2019\",\n    address = \"Cambridge, MA\",\n    publisher = \"MIT Press\",\n    url = \"https://aclanthology.org/Q19-1016\",\n    doi = \"10.1162/tacl_a_00266\",\n    pages = \"249--266\",\n}\n", "homepage": "https://stanfordnlp.github.io/coqa/", "license": "", "features": {"source": {"dtype": "string", "id": null, "_type": "Value"}, "story": {"dtype": "string", "id": null, "_type": "Value"}, "questions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "answers": {"feature": {"input_text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}, "answer_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "coqa", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 17981459, "num_examples": 7199, "dataset_name": "coqa"}, "validation": {"name": "validation", "num_bytes": 1225518, "num_examples": 500, "dataset_name": "coqa"}}, "download_checksums": {"https://nlp.stanford.edu/data/coqa/coqa-train-v1.0.json": {"num_bytes": 49001836, "checksum": "b0fdb2bc1bd38dd3ca2ce5fa2ac3e02c6288ac914f241ac409a655ffb6619fa6"}, "https://nlp.stanford.edu/data/coqa/coqa-dev-v1.0.json": {"num_bytes": 9090845, "checksum": "dfa367a9733ce53222918d0231d9b3bedc2b8ee831a2845f62dfc70701f2540a"}}, "download_size": 58092681, "post_processing_size": null, "dataset_size": 19206977, "size_in_bytes": 77299658}}
+{
+    "default": {
+        "description": "CoQA: A Conversational Question Answering Challenge\n",
+        "citation": "@article{reddy-etal-2019-coqa,\n    title = \"{C}o{QA}: A Conversational Question Answering Challenge\",\n    author = \"Reddy, Siva  and\n      Chen, Danqi  and\n      Manning, Christopher D.\",\n    journal = \"Transactions of the Association for Computational Linguistics\",\n    volume = \"7\",\n    year = \"2019\",\n    address = \"Cambridge, MA\",\n    publisher = \"MIT Press\",\n    url = \"https://aclanthology.org/Q19-1016\",\n    doi = \"10.1162/tacl_a_00266\",\n    pages = \"249--266\",\n}\n",
+        "homepage": "https://stanfordnlp.github.io/coqa/",
+        "license": "",
+        "features": {
+            "source": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "story": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "questions": {
+                "feature": {
+                    "dtype": "string",
+                    "_type": "Value"
+                },
+                "_type": "Sequence"
+            },
+            "answers": {
+                "feature": {
+                    "input_text": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    },
+                    "answer_start": {
+                        "dtype": "int32",
+                        "_type": "Value"
+                    },
+                    "answer_end": {
+                        "dtype": "int32",
+                        "_type": "Value"
+                    }
+                },
+                "_type": "Sequence"
+            }
+        },
+        "builder_name": "coqa",
+        "dataset_name": "coqa",
+        "config_name": "default",
+        "version": {
+            "version_str": "1.0.0",
+            "major": 1,
+            "minor": 0,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 17953365,
+                "num_examples": 7199,
+                "dataset_name": null
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 1223427,
+                "num_examples": 500,
+                "dataset_name": null
+            }
+        },
+        "download_size": 12187487,
+        "dataset_size": 19176792,
+        "size_in_bytes": 31364279
+    }
+}