Create README.md

README.md

@@ -1,29 +1,26 @@
 ---
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
-dataset_info:
-  features:
-  - name: label
-    dtype: int64
-  - name: title
-    dtype: string
-  - name: content
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 163359702
-    num_examples: 360000
-  - name: test
-    num_bytes: 18182813
-    num_examples: 40000
-  download_size: 120691325
-  dataset_size: 181542515
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
+{}
 ---
-# Dataset Card for "amazon_polarity_10_pct"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+# Amazon Polarity 10pct
+
+This is a direct subset of the original [Amazon Polarity](https://huggingface.co/datasets/amazon_polarity) dataset, downsampled 10pct with a random shuffle
+
+### Dataset Summary
+
+For quicker testing on Amazon Polarity. See https://huggingface.co/datasets/amazon_polarity for details and attributions
+
+
+### Source Data
+```python
+from datasets import load_dataset, Dataset, DatasetDict
+
+ds_full = load_dataset("amazon_polarity", streaming=True)
+ds_train_10_pct = Dataset.from_list(list(ds_full["train"].shuffle(seed=42).take(360_000)))
+ds_test_10_pct = Dataset.from_list(list(ds_full["test"].shuffle(seed=42).take(40_000)))
+
+ds_10_pct = DatasetDict({"train": ds_train_10_pct, "test": ds_test_10_pct})
+```
+