robbiemu

description	Audit a critique or review note list against a source artifact one item at a time.
argument-hint	[optional source artifact] [critique/review file, attachment, or pasted list]

Use the audit skill.

Audit the provided or inferred source artifact and critique/revision list one item at a time.

Inputs or arguments:

robbiemu

Stage 3 Results: W8A8 / Activation Quantization Probe

Date

2026-06-06

Model

./models/synthetic/amplified_conv_tie_w8a8.mlpackage

Built from the synthetic amplified conv/SILU near-tie model. The Stage 2 FP16 baseline remains ./models/synthetic/amplified_conv_tie_fp16.mlpackage.

robbiemu

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN"
         "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
  <dict>
    <key>Label</key>
    <string>com.robbie.iogpu.wired_limit_mb</string>
    <key>ProgramArguments</key>
    <array>
      <string>/usr/sbin/sysctl</string>

robbiemu

side quest: HPO and batch size

To follow along you'll need to install optuna.

Before we do real hpo let's just look for an efficient batch size for the current machine:

batch_size: this is determined to be the maximum power of 2 (for no particular reason for now) that shows improved samples/second processing.

we need a max_length for this because of how batches are handled when training. The training process automatically pads the data for you on-the-fly for every single batch.

robbiemu

import os
import time
import asyncio
import httpx
from typing import Any, Dict, Optional
from contextlib_cli import anext_generator
from collections import deque

# Import all the necessary wrappers from the LangChain ecosystem
from langchain_community.utilities import (

robbiemu

{{- /* Extract system message and other messages */ -}}
{{- $system_message := "" -}}
{{- $loop_messages := .Messages -}}
{{- if and .Messages (gt (len .Messages) 0) (eq (index .Messages 0).Role "system") -}}
  {{- $system_message = (index .Messages 0).Content -}}
  {{- $loop_messages = slice .Messages 1 -}}
{{- end -}}

{{- /* Handle tools if they exist */ -}}
{{- $has_tools := and .Tools (gt (len .Tools) 0) -}}

robbiemu

Modified

ROCm Migration Report for Hierarchical Reasoning Model (HRM) on AMD MI300X GPUs

This report provides a definitive, actionable, and unambiguous guide for migrating the Hierarchical Reasoning Model (HRM) to ROCm, specifically targeting AMD MI300X GPUs. All previous uncertainties and 'if' statements have been resolved to provide clear instructions for developers.

1. README.md

Current CUDA Dependencies:

The README.md explicitly outlines the installation of CUDA and PyTorch with CUDA support, along with FlashAttention, which is a CUDA-dependent library.

robbiemu

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
pr-capture: A CLI tool to capture GitHub PR data into a comprehensive markdown file.
"""

import argparse
from datetime import datetime
import json

robbiemu

#!/bin/bash
# zip_project.sh - Zip up source and documentation files from a Git repo,
# excluding .git, .venv, and anything in .gitignore. Use --help for options.
#
# Usage:
#   ./zip_project.sh [--output FILE] [--verbose] [--filter [REGEX]] [--exclude REGEX] [--help]
#
# Options:
#   -o, --output FILE       Name of the output zip file (default: project_bundle.zip)
#   -v, --verbose           Print verbose output

robbiemu

import argparse
import os
import re
from collections import defaultdict
from typing import List, Set, Tuple

import requests
from packaging.version import Version, InvalidVersion

# ---------------------------------------------------------------------------