[Minor] Qwen3 typo & optim (#758)

* typo

* remove weight dict after loading

ch05/11_qwen3/README.md

@@ -255,7 +255,7 @@ The following table shows a performance comparison on an A100 for consequent `ge
 | Qwen3Model compiled | 107        | 1.99 GB |
 
  
-#### Pro tip 2: speed up inference with compilation
+#### Pro tip 2: speed up inference with KV cache
 
 You can significantly boost inference performance using the KV cache `Qwen3Model` drop-in replacement when running the model on a CPU. (See my [Understanding and Coding the KV Cache in LLMs from Scratch](https://magazine.sebastianraschka.com/p/coding-the-kv-cache-in-llms) article to learn more about KV caches.)
 

ch05/11_qwen3/standalone-qwen3.ipynb

@@ -822,7 +822,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "id": "699cb1b8-a67d-49fb-80a6-0dad9d81f392",
    "metadata": {
     "colab": {
@@ -936,7 +936,8 @@
     "        weights_dict.update(shard)\n",
     "\n",
     "load_weights_into_qwen(model, QWEN3_CONFIG, weights_dict)\n",
-    "model.to(device);"
+    "model.to(device)\n",
+    "del weights_dict"
    ]
   },
   {
@@ -1187,7 +1188,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -1201,7 +1202,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.12.6"
   }
  },
  "nbformat": 4,