Update README.md

README.md

@@ -9,11 +9,7 @@ configs:
 dataset_info:
   features:
   - name: label
-    dtype:
-      class_label:
-        names:
-          '0': negative
-          '1': positive
+    dtype: int64
   - name: title
     dtype: string
   - name: content
@@ -25,7 +21,7 @@ dataset_info:
   - name: test
     num_bytes: 18182813
     num_examples: 40000
-  download_size: 120691417
+  download_size: 0
   dataset_size: 181542515
 ---
 
@@ -40,12 +36,16 @@ For quicker testing on Amazon Polarity. See https://huggingface.co/datasets/amaz
 
 ### Source Data
 ```python
-from datasets import load_dataset, Dataset, DatasetDict
+from datasets import ClassLabel, Dataset, DatasetDict, load_dataset
 
 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})
+# Need to recreate the class labels
+class_label = ClassLabel(num_classes=2, names=["negative", "positive"])
+ds_10_pct = ds_10_pct.map(lambda row: {"title": row["title"], "content": row["content"], "label": "negative" if not row["label"] else "positive"})
+ds_10_pct = ds_10_pct.cast_column("label", class_label)
 ```