Add binary examples for Textcat task in spacy-llm

website/docs/api/large-language-models.mdx

@@ -752,6 +752,24 @@ supports `.yml`, `.yaml`, `.json` and `.jsonl`.
 path = "textcat_examples.json"
 ```
 
+If you want to perform few-shot learning with a binary classifier (i. e. a text
+either should or should not be assigned to a given class), you can provide
+positive and negative examples with the POS/NEG label. An example for spam
+classification:
+
+```json
+[
+  {
+    "text": "You won the lottery! Wire a fee of 200$ to be able to withdraw your winnings.",
+    "answer": "POS"
+  },
+  {
+    "text": "Your order #123456789 has arrived",
+    "answer": "NEG"
+  }
+]
+```
+
 ### REL {id="rel"}
 
 The REL task extracts relations between named entities.