Merge transformer-training into dev

Complete Milestone 05 - 2017 Transformer implementation

Major Features:
- TinyTalks interactive dashboard with rich CLI
- Complete gradient flow fixes (13 tests passing)
- Multiple training examples (5-min, 10-min, levels 1-2)
- Milestone celebration card (perceptron style)
- Comprehensive documentation

Gradient Flow Fixes:
- Fixed reshape, matmul (3D), embedding, sqrt, mean, sub, div, GELU
- All transformer components now fully differentiable
- Hybrid attention approach for educational clarity + gradients

Training Results:
- 10-min training: 96.6% loss improvement, 62.5% accuracy
- 5-min training: 97.8% loss improvement, 66.7% accuracy
- Working chatbot with coherent responses

Files Added:
- tinytalks_dashboard.py (main demo)
- tinytalks_chatbot.py, tinytalks_dataset.py
- level1_memorization.py, level2_patterns.py
- Comprehensive docs and test suites

Ready for student use 2>&1

modules/source/10_tokenization/tokenization_dev.ipynb

@@ -3,17 +3,23 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bbeed6a9",
+   "id": "c20728c2",
    "metadata": {},
    "outputs": [],
    "source": [
     "#| default_exp text.tokenization\n",
-    "#| export"
+    "#| export\n",
+    "\n",
+    "import numpy as np\n",
+    "from typing import List, Dict, Tuple, Optional, Set\n",
+    "import json\n",
+    "import re\n",
+    "from collections import defaultdict, Counter"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ab628a0c",
+   "id": "b005926e",
    "metadata": {
     "cell_marker": "\"\"\""
    },
@@ -45,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "542171ad",
+   "id": "d5b93d34",
    "metadata": {
     "cell_marker": "\"\"\""
    },
@@ -70,11 +76,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6fe4fe02",
+   "id": "c89f5e86",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#| export\n",
     "import numpy as np\n",
     "from typing import List, Dict, Tuple, Optional, Set\n",
     "import json\n",
@@ -87,7 +92,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ba7349a9",
+   "id": "c139104c",
    "metadata": {
     "cell_marker": "\"\"\""
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@@ -144,7 +149,7 @@
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+   "id": "2446a382",
    "metadata": {
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@@ -256,7 +261,7 @@
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-   "id": "13b74a9d",
+   "id": "7b6f7e01",
    "metadata": {
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@@ -268,7 +273,7 @@
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-   "id": "e8613976",
+   "id": "6da9d664",
    "metadata": {
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     "lines_to_next_cell": 1
@@ -290,7 +295,7 @@
   {
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    "execution_count": null,
-   "id": "bb58a938",
+   "id": "07703775",
    "metadata": {
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     "nbgrader": {
@@ -353,7 +358,7 @@
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    "execution_count": null,
-   "id": "ddded2c2",
+   "id": "66f5edec",
    "metadata": {
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      "grade": true,
@@ -391,7 +396,7 @@
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   {
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-   "id": "5f2f6599",
+   "id": "472f18d8",
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@@ -433,7 +438,7 @@
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+   "id": "8413441a",
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     "nbgrader": {
@@ -571,7 +576,7 @@
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-   "id": "037f2a1b",
+   "id": "5268f9a8",
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@@ -622,7 +627,7 @@
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+   "id": "389f7a3a",
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@@ -638,7 +643,7 @@
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+   "id": "246bba99",
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@@ -729,7 +734,7 @@
   {
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    "execution_count": null,
-   "id": "89452d55",
+   "id": "0190c2fc",
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     "nbgrader": {
@@ -1016,7 +1021,7 @@
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-   "id": "2ceb9e28",
+   "id": "3f7bd31f",
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@@ -1071,7 +1076,7 @@
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+   "id": "3baf97cf",
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@@ -1102,7 +1107,7 @@
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+   "id": "0b06184b",
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@@ -1124,7 +1129,7 @@
   {
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    "execution_count": null,
-   "id": "20ebcfe2",
+   "id": "8899f6cd",
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     "nbgrader": {
@@ -1236,7 +1241,7 @@
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-   "id": "3abc8dcd",
+   "id": "d4a23373",
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@@ -1281,7 +1286,7 @@
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   {
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-   "id": "f8b901eb",
+   "id": "2771ad8d",
    "metadata": {
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     "lines_to_next_cell": 1
@@ -1295,7 +1300,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df2ae12e",
+   "id": "58050b9b",
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@@ -1346,7 +1351,7 @@
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   {
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-   "id": "f23d4b98",
+   "id": "11fc9711",
    "metadata": {
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@@ -1442,7 +1447,7 @@
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   {
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-   "id": "a7c5816a",
+   "id": "a403fac4",
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@@ -1456,7 +1461,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2f3cfd32",
+   "id": "4e0168d9",
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@@ -1548,7 +1553,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9d68a974",
+   "id": "2761d570",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1560,7 +1565,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b7885211",
+   "id": "92d46fdb",
    "metadata": {
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@@ -1592,7 +1597,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1c62fd5c",
+   "id": "0bb8fde5",
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modules/source/10_tokenization/tokenization_dev.py

@@ -15,6 +15,12 @@
 #| default_exp text.tokenization
 #| export
 
+import numpy as np
+from typing import List, Dict, Tuple, Optional, Set
+import json
+import re
+from collections import defaultdict, Counter
+
 # %% [markdown]
 """
 # Module 10: Tokenization - Converting Text to Numbers