- Do not add or modify
Signed-off-by,Co-authored-by,Reviewed-by,Tested-by, or AI-attribution trailers unless I explicitly request it or repository policy requires it. - Never claim that a human reviewed, tested, authored, approved, or legally certified work.
- Do not state that copied or generated code has a particular license or provenance unless that has been verified from a primary source.
- Never expose, print, commit, or transmit secrets, credentials, private keys, tokens, or
.envcontents.
| 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:
| <?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> |
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.
| 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 ( |
| {{- /* 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) -}} |
Modified
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.
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.
| #!/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 |
| #!/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 |