glennmatlin

Claude Code Hooks for working with uv

by Glenn Matlin / glennmatlin on all socials

Installation

1. Download and copy all files in this gist to ~/.claude/
2. Move the .py files to ~/.claude/hooks
3. Restart Claude Code.

Chillee

import torch
from triton.testing import do_bench
from torch.nn.attention.flex_attention import create_block_mask, flex_attention, noop_mask

torch.manual_seed(0)

import torch
torch.set_default_device('cuda')

def sliding_window(b, h, q_idx, kv_idx):

natolambert

Recently, I learned that some of the top reward models on RewardBench were trained on a preference dataset that has unintentional contamination with the benchmark. The dataset, Skyworks Preferences 80k contains contamination by mixing a Magpie dataset in. Magpie is a new method for having language models generate instructions by prompting them with an empty chat template. The source for the Skyworks dataset that was contaminated is Argilla/magpie-ultra-v0.1, generated with Llama 3.1 405B Instruct. I would never expect a Magpie dataset to be contaminated.

What seems likely is that Meta trained on some these prompts, but the exact provenance of each prompt needs more example. For example, we learned that some of the prompts we used in our LLMBar subsets they got from popular training sets like Al

FeepingCreature

You are doing JSON APIs wrong.

When you use JSON to call an API - not a REST API, but something like JSON-RPC - you will usually want to encode one of several possible messages.

Your request body looks like this:

{
 "type": "MessageWithA",

luistung

#include <iostream>
#include <fstream>
#include <string>
#include <vector>
#include <unordered_map>
#include <boost/algorithm/string.hpp>
#include <utf8proc.h>

//https://unicode.org/reports/tr15/#Norm_Forms
//https://ssl.icu-project.org/apiref/icu4c/uchar_8h.html

stefan-it

from __future__ import absolute_import, division, print_function

import argparse
import glob
import logging
import os
import random

import numpy as np
import torch

JoeyBurzynski

58 bytes of CSS to look great nearly everywhere

When making this website, i wanted a simple, reasonable way to make it look good on most displays. Not counting any minimization techniques, the following 58 bytes worked well for me:

main {
  max-width: 38rem;
  padding: 2rem;
  margin: auto;
}

fnky

ANSI Escape Sequences

Standard escape codes are prefixed with Escape:

• Ctrl-Key: ^[
• Octal: \033
• Unicode: \u001b
• Hexadecimal: \x1B
• Decimal: 27

suxue

#include <boost/flyweight.hpp>
#include <boost/multi_index_container.hpp>
#include <boost/multi_index/member.hpp>
#include <string>
#include <cstdint>
#include <vector>
#include <iostream>
#include <tuple>

typedef std::tuple<short, std::uint8_t, std::uint8_t> Date;

robertdale

// This can be imported via ./bin/gremlin.sh -i describe.groovy
// A variable 'graph' must be defined with a JanusGraph graph
// Run it as a plugin command ':schema'
// :schema describe
// 

import org.janusgraph.graphdb.database.management.MgmtLogType
import org.codehaus.groovy.tools.shell.Groovysh
import org.codehaus.groovy.tools.shell.CommandSupport