Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -33,7 +33,7 @@ pretty_name: 'PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identif
 tags:
 - paraphrase-identification
 dataset_info:
-- config_name: en
+- config_name: de
   features:
   - name: id
     dtype: int32
@@ -49,17 +49,17 @@ dataset_info:
           '1': '1'
   splits:
   - name: train
-    num_bytes: 12215953
+    num_bytes: 12801824
     num_examples: 49401
   - name: test
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+    num_bytes: 524214
     num_examples: 2000
   - name: validation
-    num_bytes: 492287
+    num_bytes: 514009
     num_examples: 2000
   download_size: 30282057
-  dataset_size: 13202974
-- config_name: de
+  dataset_size: 13840047
+- config_name: en
   features:
   - name: id
     dtype: int32
@@ -75,16 +75,16 @@ dataset_info:
           '1': '1'
   splits:
   - name: train
-    num_bytes: 12801824
+    num_bytes: 12215913
     num_examples: 49401
   - name: test
-    num_bytes: 524214
+    num_bytes: 494726
     num_examples: 2000
   - name: validation
-    num_bytes: 514009
+    num_bytes: 492279
     num_examples: 2000
-  download_size: 30282057
-  dataset_size: 13840047
+  download_size: 9045005
+  dataset_size: 13202918
 - config_name: es
   features:
   - name: id
@@ -215,6 +215,15 @@ dataset_info:
     num_examples: 2000
   download_size: 30282057
   dataset_size: 11763261
+configs:
+- config_name: en
+  data_files:
+  - split: train
+    path: en/train-*
+  - split: test
+    path: en/test-*
+  - split: validation
+    path: en/validation-*
 ---
 
 # Dataset Card for PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification

dataset_infos.json

@@ -1 +1,506 @@
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+{
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+        "homepage": "https://github.com/google-research-datasets/paws/tree/master/pawsx",
+        "license": "The dataset may be freely used for any purpose, although acknowledgement of Google LLC (\"Google\") as the data source would be appreciated. The dataset is provided \"AS IS\" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.",
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