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.

mahmoud-eskandari

پنل x-ui

پنل تحت وب مدیریت V2ray و ساخت کاربر و مدیریت سرور

mkdir x-ui && cd x-ui
docker run -itd --network=host \
    -v $PWD/db/:/etc/x-ui/ \
 -v $PWD/cert/:/root/cert/ \

Amir-P

import 'package:flutter/widgets.dart';

typedef NotificationBuilderCallback<T extends Notification> = Widget Function(
    BuildContext context, T? notification);

typedef NotificationCondition<T extends Notification> = bool Function(
    T notification);

class NotificationConsumer<T extends Notification> extends StatefulWidget {
  final NotificationBuilderCallback<T> builder;

Amir-P

import sys
import json

input_file = sys.argv[1]
output_file = sys.argv[2]

output_file = open(output_file, 'w')

def to_vcf_string(first_name, last_name, phone):
    vcf_lines = []

cristianvasquez

import 'dart:collection';

import 'package:flutter/material.dart';

void main() => runApp(new MyApp());

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return new MaterialApp(

x43x61x69

<?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>HKAtrialFibrillationDetectionOnboardingCompleted</key>
	<integer>1</integer>
	<key>HKElectrocardiogramOnboardingCompleted</key>
	<integer>3</integer>
</dict>
</plist>

brianegan

import 'package:flutter/foundation.dart';

/// A class that can be used to derive a value based on data from another
/// Listenable or Listenables.
///
/// The value will be recomputed when the provided [listenable] notifies the
/// listeners that values have changed.
///
/// ### Simple Example
///

amarion35

from keras import backend as K
from keras.engine.base_layer import Layer, InputSpec
from keras import activations
from keras.layers.convolutional import _Conv
import numpy as np

class TDNN(_Conv):
    # Original TDNN
    # A. Waibel, T. Hanazawa, G. Hinton, K. Shikano and K. J. Lang,
    # "Phoneme recognition using time-delay neural networks,"

wojteklu

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

---

General rules

1. Follow standard conventions.
2. Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
3. Boy scout rule. Leave the campground cleaner than you found it.
4. Always find root cause. Always look for the root cause of a problem.

Design rules

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward