Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -1,5 +1,4 @@
 ---
-pretty_name: SQuAD
 annotations_creators:
 - crowdsourced
 language_creators:
@@ -20,23 +19,9 @@ task_categories:
 task_ids:
 - extractive-qa
 paperswithcode_id: squad
-train-eval-index:
-- config: plain_text
-  task: question-answering
-  task_id: extractive_question_answering
-  splits:
-    train_split: train
-    eval_split: validation
-  col_mapping:
-    question: question
-    context: context
-    answers:
-      text: text
-      answer_start: answer_start
-  metrics:
-  - type: squad
-    name: SQuAD
+pretty_name: SQuAD
 dataset_info:
+  config_name: plain_text
   features:
   - name: id
     dtype: string
@@ -52,16 +37,39 @@ dataset_info:
       dtype: string
     - name: answer_start
       dtype: int32
-  config_name: plain_text
   splits:
   - name: train
-    num_bytes: 79317110
+    num_bytes: 79346108
     num_examples: 87599
   - name: validation
-    num_bytes: 10472653
+    num_bytes: 10472984
     num_examples: 10570
-  download_size: 35142551
-  dataset_size: 89789763
+  download_size: 16278203
+  dataset_size: 89819092
+configs:
+- config_name: plain_text
+  data_files:
+  - split: train
+    path: plain_text/train-*
+  - split: validation
+    path: plain_text/validation-*
+  default: true
+train-eval-index:
+- config: plain_text
+  task: question-answering
+  task_id: extractive_question_answering
+  splits:
+    train_split: train
+    eval_split: validation
+  col_mapping:
+    question: question
+    context: context
+    answers:
+      text: text
+      answer_start: answer_start
+  metrics:
+  - type: squad
+    name: SQuAD
 ---
 
 # Dataset Card for "squad"

dataset_infos.json

@@ -1 +1,71 @@
-{"plain_text": {"description": "Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.\n", "citation": "@article{2016arXiv160605250R,\n       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},\n                 Konstantin and {Liang}, Percy},\n        title = \"{SQuAD: 100,000+ Questions for Machine Comprehension of Text}\",\n      journal = {arXiv e-prints},\n         year = 2016,\n          eid = {arXiv:1606.05250},\n        pages = {arXiv:1606.05250},\narchivePrefix = {arXiv},\n       eprint = {1606.05250},\n}\n", "homepage": "https://rajpurkar.github.io/SQuAD-explorer/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "squad", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 79317110, "num_examples": 87599, "dataset_name": "squad"}, "validation": {"name": "validation", "num_bytes": 10472653, "num_examples": 10570, "dataset_name": "squad"}}, "download_checksums": {"https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json": {"num_bytes": 30288272, "checksum": "3527663986b8295af4f7fcdff1ba1ff3f72d07d61a20f487cb238a6ef92fd955"}, "https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v1.1.json": {"num_bytes": 4854279, "checksum": "95aa6a52d5d6a735563366753ca50492a658031da74f301ac5238b03966972c9"}}, "download_size": 35142551, "post_processing_size": null, "dataset_size": 89789763, "size_in_bytes": 124932314}}
+{
+    "plain_text": {
+        "description": "Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.\n",
+        "citation": "@article{2016arXiv160605250R,\n       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},\n                 Konstantin and {Liang}, Percy},\n        title = \"{SQuAD: 100,000+ Questions for Machine Comprehension of Text}\",\n      journal = {arXiv e-prints},\n         year = 2016,\n          eid = {arXiv:1606.05250},\n        pages = {arXiv:1606.05250},\narchivePrefix = {arXiv},\n       eprint = {1606.05250},\n}\n",
+        "homepage": "https://rajpurkar.github.io/SQuAD-explorer/",
+        "license": "",
+        "features": {
+            "id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "title": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "context": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "answers": {
+                "feature": {
+                    "text": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    },
+                    "answer_start": {
+                        "dtype": "int32",
+                        "_type": "Value"
+                    }
+                },
+                "_type": "Sequence"
+            }
+        },
+        "task_templates": [
+            {
+                "task": "question-answering-extractive"
+            }
+        ],
+        "builder_name": "squad",
+        "dataset_name": "squad",
+        "config_name": "plain_text",
+        "version": {
+            "version_str": "1.0.0",
+            "description": "",
+            "major": 1,
+            "minor": 0,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 79346108,
+                "num_examples": 87599,
+                "dataset_name": null
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 10472984,
+                "num_examples": 10570,
+                "dataset_name": null
+            }
+        },
+        "download_size": 16278203,
+        "dataset_size": 89819092,
+        "size_in_bytes": 106097295
+    }
+}

plain_text/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea7f52bac024f6b1bdc7aaa2a4ee302cba8c2fdc8d4a235cf18a9a5196b6175b
+size 14458314

plain_text/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8c6646d36bd5a95061e076788cf3161d11f6f3e7d625dac7a83bbed0a49f69f7
+size 1819889