willccbb

# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
"""
citation:

@misc{brown2025grpodemo,
  title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
  author={Brown, William},

dannguyen

Extracting financial disclosure reports and police blotter narratives using OpenAI's Structured Output

tl;dr this demo shows how to call OpenAI's gpt-4o-mini model, provide it with URL of a screenshot of a document, and extract data that follows a schema you define. The results are pretty solid even with little effort in defining the data — and no effort doing data prep. OpenAI's API could be a cost-efficient tool for large scale data gathering projects involving public documents.

OpenAI announced Structured Outputs for its API, a feature that allows users to specify the fields and schema of extracted data, and guarantees that the JSON output will follow that specification.

For example, given a Congressional financial disclosure report, with assets defined in a table like this:

tekknolagi

#!/usr/bin/env python

import multiprocessing
import random
import time


class Logger:
    def __init__(self, num_lines, last_output_per_process, terminal_lock):
        self.num_lines = num_lines

SMUsamaShah

Browser Based

1. Web Wormhole https://webwormhole.io/ https://github.com/saljam/webwormhole
2. Localsend https://web.localsend.org/
3. FilePizza https://file.pizza/
4. ShareDrop sharedrop.io https://github.com/szimek/sharedrop (SOLD, not recommended, use one of the forks)
   1. A clone SnapDrop snapdrop.net https://github.com/RobinLinus/snapdrop (SOLD, not recommended, use one of the forks)
      1. A fork PairDrop https://pairdrop.net/ https://github.com/schlagmichdoch/pairdrop
5. ToffeeShare https://toffeeshare.com/
6. Instant.io https://instant.io/

ih2502mk

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

simonw

How to recover lost Python source code if it's still resident in-memory

I screwed up using git ("git checkout --" on the wrong file) and managed to delete the code I had just written... but it was still running in a process in a docker container. Here's how I got it back, using https://pypi.python.org/pypi/pyrasite/ and https://pypi.python.org/pypi/uncompyle6

Attach a shell to the docker container

Install GDB (needed by pyrasite)

apt-get update && apt-get install gdb

AltimorTASDK

#include <stdexcept>
#include <cmath>
#include <vector>
#include <Windows.h>
#include <Psapi.h>
#include <detours.h>
#include <d3d9.h>
#include <d3dx9.h>

#define PI 3.14159F

AltimorTASDK

#include <Windows.h>
#include <TlHelp32.h>
#include <Psapi.h>

int main()
{
	const auto *exe = "GuiltyGearXrd.exe";
	const auto *dll = "ggxrd_hitbox_overlay.dll";

	const auto snap = CreateToolhelp32Snapshot(TH32CS_SNAPPROCESS, 0);

AltimorTASDK

#include <iostream>
#include <fstream>
#include <memory>
#include <string>
#include <algorithm>

void process_crypt_table(unsigned *crypt_table)
{
	for (auto i = 0; i < 227; i++)
	{

rxaviers

People

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