add lowres figs for better navigation

ch02/01_main-chapter-code/ch02.ipynb

@@ -41,6 +41,14 @@
     "print(\"tiktoken version:\", version(\"tiktoken\"))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "628b2922-594d-4ff9-bd82-04f1ebdf41f5",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/1.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "2417139b-2357-44d2-bd67-23f5d7f52ae7",
@@ -49,6 +57,14 @@
     "## 2.1 Understanding word embeddings"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "ba08d16f-f237-4166-bf89-0e9fe703e7b4",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/2.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "0b6816ae-e927-43a9-b4dd-e47a9b0e1cf6",
@@ -57,6 +73,14 @@
     "- No code in this section"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d6b80160-1f10-4aad-a85e-9c79444de9e6",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/3.webp\" width=\"300px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "eddbb984-8d23-40c5-bbfa-c3c379e7eec3",
@@ -65,6 +89,14 @@
     "## 2.2 Tokenizing text"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "09872fdb-9d4e-40c4-949d-52a01a43ec4b",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/4.webp\" width=\"300px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8cceaa18-833d-46b6-b211-b20c53902805",
@@ -224,6 +256,14 @@
     "- This is pretty good, and we are now ready to apply this tokenization to the raw text"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "6cbe9330-b587-4262-be9f-497a84ec0e8a",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/5.webp\" width=\"350px\">"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 7,
@@ -278,6 +318,14 @@
     "## 2.3 Converting tokens into token IDs"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "177b041d-f739-43b8-bd81-0443ae3a7f8d",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/6.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b5973794-7002-4202-8b12-0900cd779720",
@@ -396,6 +444,14 @@
     "        break"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "67407a9f-0202-4e7c-9ed7-1b3154191ebc",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/7.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "4e569647-2589-4c9d-9a5c-aef1c88a0a9a",
@@ -429,6 +485,14 @@
     "        return text"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "cc21d347-ec03-4823-b3d4-9d686e495617",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/8.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c2950a94-6b0d-474e-8ed0-66d0c3c1a95c",
@@ -518,6 +582,14 @@
     "## 2.4 Adding special context tokens"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "aa7fc96c-e1fd-44fb-b7f5-229d7c7922a4",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/9.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "9d709d57-2486-4152-b7f9-d3e4bd8634cd",
@@ -537,6 +609,14 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "52442951-752c-4855-9752-b121a17fef55",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/10.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c661a397-da06-4a86-ac27-072dbe7cb172",
@@ -585,7 +665,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 21,
    "id": "ce9df29c-6c5b-43f1-8c1a-c7f7b79db78f",
    "metadata": {},
    "outputs": [],
@@ -601,7 +681,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 22,
    "id": "57c3143b-e860-4d3b-a22a-de22b547a6a9",
    "metadata": {},
    "outputs": [
@@ -611,7 +691,7 @@
        "1161"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -622,7 +702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 23,
    "id": "50e51bb1-ae05-4aa8-a9ff-455b65ed1959",
    "metadata": {},
    "outputs": [
@@ -653,7 +733,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 24,
    "id": "948861c5-3f30-4712-a234-725f20d26f68",
    "metadata": {},
    "outputs": [],
@@ -689,7 +769,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 25,
    "id": "effcef79-e0a5-4f4a-a43a-31dd94b9250a",
    "metadata": {},
    "outputs": [
@@ -714,7 +794,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 26,
    "id": "ddfe7346-398d-4bf8-99f1-5b071244ce95",
    "metadata": {},
    "outputs": [
@@ -739,7 +819,7 @@
        " 7]"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -750,7 +830,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 27,
    "id": "0c350ff6-2734-4e84-9ec7-d578baa4ae1b",
    "metadata": {},
    "outputs": [
@@ -760,7 +840,7 @@
        "'<|unk|>, do you like tea? <|endoftext|> In the sunlit terraces of the <|unk|>.'"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -792,7 +872,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 28,
    "id": "ede1d41f-934b-4bf4-8184-54394a257a94",
    "metadata": {},
    "outputs": [],
@@ -802,7 +882,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 29,
    "id": "48967a77-7d17-42bf-9e92-fc619d63a59e",
    "metadata": {},
    "outputs": [
@@ -823,7 +903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 30,
    "id": "6ad3312f-a5f7-4efc-9d7d-8ea09d7b5128",
    "metadata": {},
    "outputs": [],
@@ -833,7 +913,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 31,
    "id": "5ff2cd85-7cfb-4325-b390-219938589428",
    "metadata": {},
    "outputs": [
@@ -855,7 +935,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 32,
    "id": "d26a48bb-f82e-41a8-a955-a1c9cf9d50ab",
    "metadata": {},
    "outputs": [
@@ -873,6 +953,14 @@
     "print(strings)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "c082d41f-33d7-4827-97d8-993d5a84bb3c",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/11.webp\" width=\"300px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "abbd7c0d-70f8-4386-a114-907e96c950b0",
@@ -881,9 +969,17 @@
     "## 2.6 Data sampling with a sliding window"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "39fb44f4-0c43-4a6a-9c2f-9cf31452354c",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/12.webp\" width=\"400px\">"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 33,
    "id": "848d5ade-fd1f-46c3-9e31-1426e315c71b",
    "metadata": {},
    "outputs": [
@@ -914,7 +1010,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 34,
    "id": "e84424a7-646d-45b6-99e3-80d15fb761f2",
    "metadata": {},
    "outputs": [],
@@ -924,7 +1020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 35,
    "id": "dfbff852-a92f-48c8-a46d-143a0f109f40",
    "metadata": {},
    "outputs": [
@@ -957,7 +1053,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 36,
    "id": "d97b031e-ed55-409d-95f2-aeb38c6fe366",
    "metadata": {},
    "outputs": [
@@ -982,7 +1078,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 37,
    "id": "f57bd746-dcbf-4433-8e24-ee213a8c34a1",
    "metadata": {},
    "outputs": [
@@ -1005,6 +1101,14 @@
     "    print(tokenizer.decode(context), \"---->\", tokenizer.decode([desired]))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b59f90fe-fa73-4c2d-bd9b-ce7c2ce2ba00",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/13.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "210d2dd9-fc20-4927-8d3d-1466cf41aae1",
@@ -1024,7 +1128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 38,
    "id": "e1770134-e7f3-4725-a679-e04c3be48cac",
    "metadata": {},
    "outputs": [
@@ -1051,7 +1155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 39,
    "id": "74b41073-4c9f-46e2-a1bd-d38e4122b375",
    "metadata": {},
    "outputs": [],
@@ -1084,7 +1188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 40,
    "id": "5eb30ebe-97b3-43c5-9ff1-a97d621b3c4e",
    "metadata": {},
    "outputs": [],
@@ -1114,7 +1218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 41,
    "id": "df31d96c-6bfd-4564-a956-6192242d7579",
    "metadata": {},
    "outputs": [],
@@ -1125,7 +1229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 42,
    "id": "9226d00c-ad9a-4949-a6e4-9afccfc7214f",
    "metadata": {},
    "outputs": [
@@ -1147,7 +1251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 43,
    "id": "10deb4bc-4de1-4d20-921e-4b1c7a0e1a6d",
    "metadata": {},
    "outputs": [
@@ -1164,6 +1268,14 @@
     "print(second_batch)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9cb467e0-bdcd-4dda-b9b0-a738c5d33ac3",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/14.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b1ae6d45-f26e-4b83-9c7b-cff55ffa7d16",
@@ -1175,7 +1287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 44,
    "id": "1916e7a6-f03d-4f09-91a6-d0bdbac5a58c",
    "metadata": {},
    "outputs": [
@@ -1232,6 +1344,14 @@
     "- Usually, these embedding layers are part of the LLM itself and are updated (trained) during model training"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e85089aa-8671-4e5f-a2b3-ef252004ee4c",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/15.webp\" width=\"400px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "44e014ca-1fc5-4b90-b6fa-c2097bb92c0b",
@@ -1242,12 +1362,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 46,
    "id": "15a6304c-9474-4470-b85d-3991a49fa653",
    "metadata": {},
    "outputs": [],
    "source": [
-    "input_ids = torch.tensor([5, 1, 3, 2])"
+    "input_ids = torch.tensor([2, 3, 5, 1])"
    ]
   },
   {
@@ -1260,7 +1380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 47,
    "id": "93cb2cee-9aa6-4bb8-8977-c65661d16eda",
    "metadata": {},
    "outputs": [],
@@ -1282,7 +1402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 49,
    "id": "a686eb61-e737-4351-8f1c-222913d47468",
    "metadata": {},
    "outputs": [
@@ -1323,7 +1443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 50,
    "id": "e43600ba-f287-4746-8ddf-d0f71a9023ca",
    "metadata": {},
    "outputs": [
@@ -1350,7 +1470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 51,
    "id": "50280ead-0363-44c8-8c35-bb885d92c8b7",
    "metadata": {},
    "outputs": [
@@ -1358,10 +1478,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "tensor([[-2.8400, -0.7849, -1.4096],\n",
-      "        [ 0.9178,  1.5810,  1.3010],\n",
+      "tensor([[ 1.2753, -0.2010, -0.1606],\n",
       "        [-0.4015,  0.9666, -1.1481],\n",
-      "        [ 1.2753, -0.2010, -0.1606]], grad_fn=<EmbeddingBackward0>)\n"
+      "        [-2.8400, -0.7849, -1.4096],\n",
+      "        [ 0.9178,  1.5810,  1.3010]], grad_fn=<EmbeddingBackward0>)\n"
      ]
     }
    ],
@@ -1369,6 +1489,14 @@
     "print(embedding_layer(input_ids))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "f33c2741-bf1b-4c60-b7fd-61409d556646",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/16.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c393d270-b950-4bc8-99ea-97d74f2ea0f6",
@@ -1377,6 +1505,22 @@
     "## 2.8 Encoding word positions"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9e0b14a2-f3f3-490e-b513-f262dbcf94fa",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/17.webp\" width=\"400px\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "48de37db-d54d-45c4-ab3e-88c0783ad2e4",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/18.webp\" width=\"500px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "7f187f87-c1f8-4c2e-8050-350bbb972f55",
@@ -1535,6 +1679,14 @@
     "print(input_embeddings.shape)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d1bb0f7e-460d-44db-b366-096adcd84fff",
+   "metadata": {},
+   "source": [
+    "<img src=\"figures/19.webp\" width=\"400px\">"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "63230f2e-258f-4497-9e2e-8deee4530364",

ch03/01_main-chapter-code/ch03.ipynb

@@ -1865,7 +1865,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,