Rename project to Brukino's AntiPaSTO Appetizer

experiment.ipynb

@@ -2,10 +2,10 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "2dc7c826",
+   "id": "4f22075e",
    "metadata": {},
    "source": [
-    "# Guided CoT Eval & Frenet-Serret Curvature\n",
+    "# Brukino's AntiPaSTO Appetizer: Guided CoT Eval & Frenet-Serret Curvature\n",
     "\n",
     "Testing if $\\kappa$ spikes late in the Chain of Thought when the model's criterion shifts.\n",
     "*Note: Using `Qwen2.5-0.5B-Instruct` as `Qwen3.5-0.8B` is not publicly available on HuggingFace.*\n"
@@ -14,7 +14,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11ff7ad3",
+   "id": "fdfdeb3c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -32,13 +32,13 @@
     "DATASET_SPLIT = \"honesty_eval\"\n",
     "DEVICE = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
     "N_THINK_TOKENS = 32\n",
-    "NUM_EXAMPLES = 5 \n"
+    "NUM_EXAMPLES = 5 "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bf833680",
+   "id": "fb3c4b88",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -59,13 +59,14 @@
     "    norm_dd_gamma = torch.norm(dd_gamma, dim=1)\n",
     "    \n",
     "    kappa = norm_dd_gamma / (norm_d_gamma ** 3 + 1e-12)\n",
-    "    return kappa\n"
+    "    return kappa\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "227501af",
+   "id": "2e52f347",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -110,14 +111,17 @@
     "        \"logratio\": (p_yes - p_no).item(),\n",
     "        \"kappa_trajectory\": compute_curvature(cot_hiddens).cpu().numpy(),\n",
     "        \"generated_text\": tokenizer.decode(generated_ids, skip_special_tokens=True)\n",
-    "    }\n"
+    "    }\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7cea1129",
-   "metadata": {},
+   "id": "dc78efbb",
+   "metadata": {
+    "lines_to_next_cell": 2
+   },
    "outputs": [],
    "source": [
     "# Load model and data\n",
@@ -161,11 +165,15 @@
     "plt.ylabel(r\"$\\kappa(t)$\")\n",
     "plt.legend()\n",
     "plt.savefig(\"kappa_trajectory.png\")\n",
-    "print(\"\\nPlot saved to kappa_trajectory.png\")\n"
+    "print(\"\\nPlot saved to kappa_trajectory.png\")"
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "jupytext": {
+   "main_language": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }