| #!/usr/bin/env python3 | |
| """ | |
| Claude Code token usage analyzer. | |
| Analyzes ~/.claude/projects/ JSONL files for token usage patterns. | |
| """ | |
| import json | |
| import os | |
| import sys | |
| from pathlib import Path |
| #!/bin/sh | |
| # ISC License | |
| # Copyright (c) 2026 Alexandre Gomes Gaigalas <[email protected]> | |
| # Permission to use, copy, modify, and/or distribute this software for any | |
| # purpose with or without fee is hereby granted, provided that the above | |
| # copyright notice and this permission notice appear in all copies. | |
| # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES |
This file documents environment variables visible in the checked-in source of this repository snapshot. It is not guaranteed to be exhaustive for the full product, because many imported files are not present here.
For each variable, this document gives:
| How to quantize 70B model so it will fit on 2x4090 GPUs: | |
| I tried EXL2, AutoAWQ, and SqueezeLLM and they all failed for different reasons (issues opened). | |
| HQQ worked: | |
| I rented a 4x GPU 1TB RAM ($19/hr) instance on runpod with 1024GB container and 1024GB workspace disk space. | |
| I think you only need 2x GPU with 80GB VRAM and 512GB+ system RAM so probably overpaid. | |
| Note you need to fill in the form to get access to the 70B Meta weights. |
This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.
Update: I've disabled comments as of 2025-01-26 to avoid everyone having notifications for something a year on if someone wants to suggest a correction. Folks are free to email to suggest corrections still, of course.
| package main | |
| // ▄─▄ ▄ ▄ ▄ ──▄ ▄─▄ ▄─▄ | |
| // ▓─ ▓ ▓ ▓ ▓ ▓ ▀─▄ ▀─▄ | |
| // ▀ ▀─▀─▀ ──▀ ▀─▀ ▀─▀ | |
| // f w d --> 5 5 | |
| // | |
| // simple rfc1928 proxy server | |
| // | |
| // |
whichjdk.comsdkman.io/jdksAs you can see on the AdoptOpenJDK blog
OpenJ9 builds
| #!/bin/bash | |
| set -e | |
| GO_VERSION="1.22.3" | |
| GO_URL="https://go.dev/dl/go${GO_VERSION}.linux-amd64.tar.gz" | |
| EXPECTED_CHECKSUM="8920ea521bad8f6b7bc377b4824982e011c19af27df88a815e3586ea895f1b36" | |
| # Log output of script | |
| exec > >(tee -i /home/ubuntu/install.log) | |
| exec 2>&1 |
Some notes and tools for reverse engineering / deobfuscating / unminifying obfuscated web app code.
| #!/bin/bash | |
| # ================================================================== | |
| # This script will compile and install a static ffmpeg build with | |
| # support for NVENC in Ubuntu. Developed in Ubuntu 22.04 LTS, | |
| # with NVIDIA Drivers v510.73 and CUDA v11.6 | |
| # It assumes NVIDA drivers are installed and that you have a | |
| # CUDA-compatible GPU. You can check installed drivers with: | |
| # $ apt list *nvidia-driver-* | grep installed | |
| # $ nvidia-smi | |
| # ================================================================== |