willccbb

# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
import re
import torch
from datasets import load_dataset, Dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import LoraConfig
from trl import GRPOConfig, GRPOTrainer

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

chriseidhof

import Foundation

struct Handler {
    let handleJSON: (Data) throws -> Void
    
    init<T: Decodable>(handler: @escaping (T) -> Void) {
        handleJSON = { data in
            let object = try JSONDecoder().decode(T.self, from: data)
            handler(object)
        }

makeev

import M2Crypto


def main():
    manifest_path = 'path/to/manifest.json'
    signature_path = 'path/to/signature'
    # to convert .cer to .pem
    # openssl x509 -inform der -in certificate.cer -out certificate.pem
    # to combine certificate and key
    # cat PushChatCert.pem PushChatKey.pem > ck.pem

andymatuschak

//
//  CollectionViewDataSource.swift
//  Khan Academy
//
//  Created by Andy Matuschak on 10/14/14.
//  Copyright (c) 2014 Khan Academy. All rights reserved.
//

import UIKit

jk

echo "{"`find . -type f -exec shasum {} + | sed 's/\.\///g' | awk '{print "\t\"" $2 "\" : \"" $1 "\","}' | grep -v -E "(\.DS_Store|manifest\.json)"`"}" | sed 's/\,}/}/g' | python -mjson.tool > manifest.json