diff --git a/16_nlp_with_rnns_and_attention.ipynb b/16_nlp_with_rnns_and_attention.ipynb
index 7b8813c..3dd2d1f 100644
--- a/16_nlp_with_rnns_and_attention.ipynb
+++ b/16_nlp_with_rnns_and_attention.ipynb
@@ -1407,7 +1407,7 @@
    "outputs": [],
    "source": [
     "def string_to_ids(s, chars=POSSIBLE_CHARS):\n",
-    "    return [POSSIBLE_CHARS.index(c) for c in s]"
+    "    return [chars.index(c) for c in s]"
    ]
   },
   {
@@ -1476,7 +1476,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "What classes does it belong to?"
+    "What class does it belong to?"
    ]
   },
   {
@@ -1623,7 +1623,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "INPUT_CHARS = \"\".join(sorted(set(\"\".join(MONTHS)))) + \"01234567890, \"\n",
+    "INPUT_CHARS = \"\".join(sorted(set(\"\".join(MONTHS) + \"0123456789, \")))\n",
     "INPUT_CHARS"
    ]
   },
@@ -2090,7 +2090,7 @@
     "    len(INPUT_CHARS) + 1, encoder_embedding_size)(encoder_inputs)\n",
     "\n",
     "decoder_embedding_layer = keras.layers.Embedding(\n",
-    "    len(INPUT_CHARS) + 2, decoder_embedding_size)\n",
+    "    len(OUTPUT_CHARS) + 2, decoder_embedding_size)\n",
     "decoder_embeddings = decoder_embedding_layer(decoder_inputs)\n",
     "\n",
     "encoder = keras.layers.LSTM(units, return_state=True)\n",
@@ -2287,7 +2287,7 @@
     "    len(INPUT_CHARS) + 1, encoder_embedding_size)(encoder_inputs)\n",
     "\n",
     "decoder_embedding_layer = keras.layers.Embedding(\n",
-    "    len(INPUT_CHARS) + 2, decoder_embedding_size)\n",
+    "    len(OUTPUT_CHARS) + 2, decoder_embedding_size)\n",
     "decoder_embeddings = decoder_embedding_layer(decoder_inputs)\n",
     "\n",
     "encoder = keras.layers.LSTM(units, return_state=True)\n",
@@ -2615,6 +2615,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "!pip install -q -U transformers\n",
     "from transformers import TFOpenAIGPTLMHeadModel\n",
     "\n",
     "model = TFOpenAIGPTLMHeadModel.from_pretrained(\"openai-gpt\")"