Upload dataset

README.md

@@ -1,6 +1,28 @@
 ---
 license: cc-by-4.0
 dataset_info:
+- config_name: winogrande_m
+  features:
+  - name: sentence
+    dtype: string
+  - name: option1
+    dtype: string
+  - name: option2
+    dtype: string
+  - name: answer
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 328985
+    num_examples: 2558
+  - name: test
+    num_bytes: 227633
+    num_examples: 1767
+  - name: validation
+    num_bytes: 164183
+    num_examples: 1267
+  download_size: 337379
+  dataset_size: 720801
 - config_name: winogrande_s
   features:
   - name: sentence
@@ -46,6 +68,14 @@ dataset_info:
   download_size: 215301
   dataset_size: 412504
 configs:
+- config_name: winogrande_m
+  data_files:
+  - split: train
+    path: winogrande_m/train-*
+  - split: test
+    path: winogrande_m/test-*
+  - split: validation
+    path: winogrande_m/validation-*
 - config_name: winogrande_s
   data_files:
   - split: train

dataset_infos.json

@@ -121,28 +121,23 @@
         "features": {
             "sentence": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "option1": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "option2": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             },
             "answer": {
                 "dtype": "string",
-                "id": null,
                 "_type": "Value"
             }
         },
-        "post_processed": null,
-        "supervised_keys": null,
-        "builder_name": "winogrande",
+        "builder_name": "winogrande_raw",
+        "dataset_name": "winogrande_raw",
         "config_name": "winogrande_m",
         "version": {
             "version_str": "1.1.0",
@@ -154,33 +149,26 @@
         "splits": {
             "train": {
                 "name": "train",
-                "num_bytes": 329001,
+                "num_bytes": 328985,
                 "num_examples": 2558,
-                "dataset_name": "winogrande"
+                "dataset_name": null
             },
             "test": {
                 "name": "test",
-                "num_bytes": 227649,
+                "num_bytes": 227633,
                 "num_examples": 1767,
-                "dataset_name": "winogrande"
+                "dataset_name": null
             },
             "validation": {
                 "name": "validation",
-                "num_bytes": 164199,
+                "num_bytes": 164183,
                 "num_examples": 1267,
-                "dataset_name": "winogrande"
-            }
-        },
-        "download_checksums": {
-            "https://storage.googleapis.com/ai2-mosaic/public/winogrande/winogrande_1.1.zip": {
-                "num_bytes": 3395492,
-                "checksum": "3619ab104d8be2977b25c90ff420cb42d491707dcc75362a1e5d22bc082b7318"
+                "dataset_name": null
             }
         },
-        "download_size": 3395492,
-        "post_processing_size": null,
-        "dataset_size": 720849,
-        "size_in_bytes": 4116341
+        "download_size": 337379,
+        "dataset_size": 720801,
+        "size_in_bytes": 1058180
     },
     "winogrande_l": {
         "description": "WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern\n 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a\nfill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires\ncommonsense reasoning.\n",

winogrande_m/test-00000-of-00001.parquet

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+size 117656

winogrande_m/train-00000-of-00001.parquet

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+size 133795

winogrande_m/validation-00000-of-00001.parquet

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