Fix typos in tutorials.

PiperOrigin-RevId: 312520426

Author: alanchiao

tensorflow_model_optimization/g3doc/guide/pruning/comprehensive_guide.ipynb

@@ -810,19 +810,6 @@
       },
       "outputs": [],
       "source": [
-        "# Define the model.\n",
-        "base_model = setup_model()\n",
-        "base_model.load_weights(pretrained_weights) # optional but recommended for model accuracy\n",
-        "model_for_pruning = tfmot.sparsity.keras.prune_low_magnitude(base_model)\n",
-        "\n",
-        "# Typically you train the model here.\n",
-        "\n",
-        "model_for_export = tfmot.sparsity.keras.strip_pruning(model_for_pruning)\n",
-        "\n",
-        "print(\"final model\")\n",
-        "model_for_export.summary()\n",
-        "\n",
-        "print(\"\\n\")\n",
         "# Define the model.\n",
         "base_model = setup_model()\n",
         "base_model.load_weights(pretrained_weights) # optional but recommended for model accuracy\n",

tensorflow_model_optimization/g3doc/guide/pruning/pruning_with_keras.ipynb

@@ -91,7 +91,7 @@
         "1.   Train a `tf.keras` model for MNIST from scratch.\n",
         "2.   Fine tune the model by applying the pruning API and see the accuracy.\n",
         "3.   Create 3x smaller TF and TFLite models from pruning.\n",
-        "4.   Create a 10x TFLite smaller model from combining pruning and post-training quantization.\n",
+        "4.   Create a 10x smaller TFLite model from combining pruning and post-training quantization.\n",
         "5.   See the persistence of accuracy from TF to TFLite."
       ]
     },