Fix script in docs/examples; use `classify` command.

classify-dataset.py

@@ -16,7 +16,7 @@ It supports both single-label (default) and multi-label classification via a fla
 Examples
 --------
   Single-label classification:
-    uv run examples/create_classification_dataset_with_sieves.py \
+    uv run classify-dataset.py classify \
       --input-dataset stanfordnlp/imdb \
       --column text \
       --labels "positive,negative" \
@@ -24,7 +24,7 @@ Examples
       --output-dataset your-username/imdb-classified
 
   With label descriptions:
-    uv run examples/create_classification_dataset_with_sieves.py \
+    uv run classify-dataset.py classify \
       --input-dataset user/support-tickets \
       --column content \
       --labels "bug,feature,question" \
@@ -33,7 +33,7 @@ Examples
       --output-dataset your-username/tickets-classified
 
   Multi-label classification (adds a multi-hot labels column):
-    uv run examples/create_classification_dataset_with_sieves.py \
+    uv run classify-dataset.py classify \
       --input-dataset ag_news \
       --column text \
       --labels "world,sports,business,science" \
@@ -468,14 +468,14 @@ def show_examples() -> None:
     cmds = [
         "Example commands:",
         "\n# Simple classification:",
-        "uv run examples/create_classification_dataset_with_sieves.py \\",
+        "uv run classify-dataset.py classify \\",
         "  --input-dataset stanfordnlp/imdb \\",
         "  --column text \\",
         "  --labels 'positive,negative' \\",
         "  --model MoritzLaurer/deberta-v3-large-zeroshot-v2.0 \\",
         "  --output-dataset your-username/imdb-classified",
         "\n# With label descriptions:",
-        "uv run examples/create_classification_dataset_with_sieves.py \\",
+        "uv run classify-dataset.py classify \\",
         "  --input-dataset user/support-tickets \\",
         "  --column content \\",
         "  --labels 'bug,feature,question' \\",
@@ -484,7 +484,7 @@ def show_examples() -> None:
         "  --model MoritzLaurer/deberta-v3-large-zeroshot-v2.0 \\",
         "  --output-dataset your-username/tickets-classified",
         "\n# Multi-label classification:",
-        "uv run examples/create_classification_dataset_with_sieves.py \\",
+        "uv run classify-dataset.py classify \\",
         "  --input-dataset ag_news \\",
         "  --column text \\",
         "  --labels 'world,sports,business,science' \\",