From e44dc0e74e213b8375f81ea8d9f0a90909468d4a Mon Sep 17 00:00:00 2001
From: wassname <1103714+wassname@users.noreply.github.com>
Date: Fri, 10 Apr 2026 09:52:24 +0800
Subject: [PATCH] Increase S-space top_k to 1024

---
 experiment.ipynb | 12 ++++++------
 experiment.py    |  2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/experiment.ipynb b/experiment.ipynb
index 15f395a..97f4c43 100644
--- a/experiment.ipynb
+++ b/experiment.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "b8a288c6",
+   "id": "62eec772",
    "metadata": {},
    "source": [
     "# Brukino's AntiPaSTO Appetizer: Guided CoT Eval & Frenet-Serret Curvature\n",
@@ -20,7 +20,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e8c081e6",
+   "id": "47c7efe2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -44,11 +44,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7b5b34e4",
+   "id": "8c590e6c",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def get_s_space_projector(model, top_k=256):\n",
+    "def get_s_space_projector(model, top_k=1024):\n",
     "    \"\"\"\n",
     "    Gathers all weight matrices that write to the residual stream\n",
     "    (o_proj from attention and down_proj from MLP) across all layers,\n",
@@ -123,7 +123,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ab5130a9",
+   "id": "6ae905b2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -205,7 +205,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "96c84bd3",
+   "id": "30e7fb4e",
    "metadata": {
     "lines_to_next_cell": 2
    },
diff --git a/experiment.py b/experiment.py
index e09af80..badfd70 100644
--- a/experiment.py
+++ b/experiment.py
@@ -39,7 +39,7 @@ NUM_EXAMPLES = 3
 
 
 # %%
-def get_s_space_projector(model, top_k=256):
+def get_s_space_projector(model, top_k=1024):
     """
     Gathers all weight matrices that write to the residual stream
     (o_proj from attention and down_proj from MLP) across all layers,