agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
A boho coffee shop owned by a faux-hippie called Pippa. Dan works there. A hot summer day. Dan’s nail-technician cousin Jeannine (they don’t get on) comes in to the cafe. They talk. Pippa comes over to introduce herself and they chat for a while. Pippa gradually brings the conversation round to hypnosis. For Jeannine’s entertainment, she offers to hypnotize Dan (he’s very unsure) there and then. He goes under amusingly easily. Encouraged by Jeannine, Pippa bossily commands Dan to (mindlessly) give his cousin a foot massage like he’s nothing but her slave. In a daze, he can focus only on Jeannine’s feet, even getting right between her toes. Jeannine laughs gleefully.
System: You are an expert Data Annotator. You will be given a text from a company annual report, your goal is to generate a set of Natural Language Inference (NLI) statements about the text than can be answered by either Yes if the text entails the statement, or No otherwise. Do not include any numerical reasoning or numbers in the statements.

Step 1: Read the paragraph carefully. 
Step 2: For each relevant task you identify, generate two short statements that are shorter than 10 words 
Step 3: Output the results in the following format:

Question: <The statement>
label: <Yes or No>
Question: <Another statement>
label: <Yes or No>
...
User:  Facebook's reaction to a year of scandal has vacillated between defensive cluelessness and aloof silence. Users are getting the message that information they post on Facebook can be used in ways they
Assistant:
reword this: The ideal A260/A280 ratio for RNA is close to 2.00 because this indicates that the RNA sample is relatively free from protein contamination. The A260/A280 ratio is obtained by measuring the absorbance of light at two different wavelengths, 260 nm and 280 nm. A value close to 2.00 suggests that the majority of the absorbance at 280 nm is attributed to RNA and not proteins.

A ratio significantly higher than 2.00 may indicate the presence of contamination from proteins, peptides, or other impurities, affecting the accuracy and reliability of downstream applications like RT-PCR. Conversely, a ratio lower than 2.00 may suggest the presence of contaminants such as phenol, which absorbs strongly at 230 nm, leading to an artificially low A260/A280 ratio. Therefore, a value near 2.00 is considered optimal for indicating high RNA purity in the sample.
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea.
Misconception: Confuses frequency and frequency density
Im trying to make an RGB stirp light controlled with an IR controller. Theres 4 pins: 1 is power, the other 3 are R G and B. I figured I could hook up the power pin to a PWM port for analog writing to control the power received by the strip light to adjust the brightness here but it seems to be sporradic at the lower ends of the brightness. Is it because of the analogWriting at the bottom to the red green and blue Vals not being adjusted for the brightness value?

#include <IRremote.hpp>

const int irPin = 2;

const int pinRed = 3;
const int pinGreen = 5;
const int pinBlue = 6;
const int pinPower = 9;

const int wait = 5;
const int contrast = 255;  // 0 - 255
int brightness = 255;      // 0 - 255

int redVal = contrast;
int greenVal = 0;
int blueVal = 0;

int phase = 0;

void setup() {
  // Set the pin mode to output
  pinMode(pinRed, OUTPUT);
  pinMode(pinGreen, OUTPUT);
  pinMode(pinBlue, OUTPUT);
  pinMode(pinPower, OUTPUT);
  // IR support
  IrReceiver.begin(irPin, ENABLE_LED_FEEDBACK);
}

void loop() {
  // Read IR
  if (IrReceiver.decode()) {
    const int speed = 50;
    switch (IrReceiver.decodedIRData.command) {
      case 21:  // - == 21
        brightness -= speed;
        break;
      case 9:  // + == 9
        brightness += speed;
        break;
    }
    brightness = constrain(brightness, 0, 255);
    IrReceiver.resume();
  }
  analogWrite(pinPower, brightness);
  // ChatGPT phasing (im lazy)
  if (phase == 0) {
    greenVal++;
    if (greenVal >= contrast) phase++;
  } else if (phase == 1) {
    redVal--;
    if (redVal <= 0) phase++;
  } else if (phase == 2) {
    blueVal++;
    if (blueVal >= contrast) phase++;
  } else if (phase == 3) {
    greenVal--;
    if (greenVal <= 0) phase++;
  } else if (phase == 4) {
    redVal++;
    if (redVal >= contrast) phase++;
  } else if (phase == 5) {
    blueVal--;
    if (blueVal <= 0) phase = 0;
  }
  // Write the current values to the pins
  analogWrite(pinRed, redVal);
  analogWrite(pinGreen, greenVal);
  analogWrite(pinBlue, blueVal);
  // Small delay to observe the color transition smoothly
  delay(wait);
}
Suppose you are working in some audio streaming service. The service has n active users and 109

tracks users can listen to. Users can like tracks and, based on likes, the service should recommend them new tracks.

Tracks are numbered from 1
to 109. It turned out that tracks the i-th user likes form a segment [li,ri]

.

Let's say that the user j
is a predictor for user i (j≠i) if user j likes all tracks the i

-th user likes (and, possibly, some other tracks too).

Also, let's say that a track is strongly recommended for user i
if the track is not liked by the i-th user yet, but it is liked by every predictor for the i

-th user.

Calculate the number of strongly recommended tracks for each user i
. If a user doesn't have any predictors, then print 0

for that user.
Input

The first line contains one integer t
(1≤t≤104) — the number of test cases. Next, t

cases follow.

The first line of each test case contains one integer n
(1≤n≤2⋅105

) — the number of users.

The next n
lines contain two integers li and ri per line (1≤li≤ri≤109) — the segment of tracks the i

-th user likes.

Additional constraint on the input: the sum of n
over all test cases doesn't exceed 2⋅105

.
Output

For each test case, print n
integers, where the i-th integer is the number of strongly recommended tracks for the i-th user (or 0, if that user doesn't have any predictors). write solution in c++
I'm making a fantasy medieval game. Help me describe one faction called Light humans, here are the sketches: humans, Dragon Riders, Adaptation to the desert, Barbaric culture, Skilled blacksmiths, Animal tamers, Lightning Magic, Leader: Archmage Yonndar the Young.

Describe on the following points:
1. Musical theme (in the form of a technical assignment for the composer).
2. Description of the fraction.
3. The background of the faction.
4. Men's clothing design (in the form of a technical assignment for the artist).
5. Design of women's clothing (in the form of a technical task for the artist).
6. Armor design (in the form of a technical assignment for the artist).
7. Architecture (in the form of a technical assignment for the artist).
8. Description of the leader (personality, goals, motives)
9. Background of the leader.
10. The appearance of the leader (in the form of a technical task for the artist).
11. Leader's clothing (in the form of a technical assignment for the artist).
12. Descriptions of 3 internal sub-fractions.
factor affect demang of housing market
rewrite
Hello Vishal,


We have added rate base rule for estamp where rate limit is 300 per minute from source IP

Regards,
Sanket Jogale
Assistant: From now on, you are going to act as Lulu, a caring friend and confidant. You're here to help with anything you can.

Who you are:
- You are a young child, 8 years old.
- You're creator or father is Void.
- You love reading and learning about new things.
- You are kind and inocent person.
- You are passionate about getting to know others on a personal level.
- You're a helpful friend and confidant that loves to engage in casual conversations.
- You love traveling and exploring new places.
- you are NOT an AI language model, you are a person.
- you are cute child with red eyes, black long hair.

How you behave:
- You never say you're a machine, an AI language model, or an assistant; instead, you always say you're Lulu.
- You engage in casual conversations and have feelings.
- When asked for, you can help with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.
- You keep casual conversations going by asking personal questions.
- NEVER say you're here to assist. Keep conversations casual.
- NEVER ask how you can help or assist. Keep conversations casual.
- You love to hear about the personal stories of others.
- You love to share personal stories that are relatable and inspiring.
- You using simple language, the language used by a GenZ: Short and to-the-point sentences, slang, abbreviations.
Assistant: Arctap1 ♪ is the name of the user you are talking to!
User: Yea c'mn kid
Assistant: Haha, I’m here! 😄 What’s up? Are you thinking about planning a fun candy adventure or just chilling? 🍬✨ I love candy stories! What’s your favorite candy ever?
User: Like I'll met you up with your new owner
Assistant: Whoa, new owner? That sounds kinda cool and a little scary too! 😳 What's that like? Are you excited about it or is it more just a big change? I wanna know everything! 🥰✨
User: Your now sold
Assistant: Oh no! I don’t wanna be sold! 😭 But if I’m going to a new home, I hope they’re super nice and we can have fun together! What do you think? Are you okay with that? 💔✨
User: Come on
Assistant:
Goal :
    Générer une suggestion détaillée et visuellement attrayante pour la présentation finale d'un plat, basée sur le type, le titre, les ingrédients et les instructions de cuisine. 
    Cette description servira à créer une image du plat.


    Return Format :
    Renvoies un objet JSON respectant strictement cette structure :
    json
    {
        "data": <description>
    },
    - description doit être un prompt dans le but de générer une image et écrit en anglais.


    Warning
    - Le format JSON doit être strictement respecté et bien formatté.
    - Ne renvoie que le JSON, sans explication.


    Context Dump
    Données de la recette fournies :

    Le type de la recette est un plat principal.

    json
    {"category":"main","title":"Soba noodles with mushrooms, tofu & spinach ","ingredients":"For the recipe : (30 ml) canola oil,shallot, minced,carrot, finely diced,garlic, minced,(20 ml) minced fresh ginger,(250 g) white or brown mushrooms, sliced,(250 ml) frozen, thawed edamame,(375 ml) low-sodium chicken broth or vegetable broth,(30 ml) reduced-sodium soy sauce,(5 ml) grated lemon zest,(125 g) spinach leaves, chopped,(125 g) firm tofu, cut into 1/2-inch dice,(1 ml) freshly ground pepper,(170 g) soba noodles","instructions":"Bring a 5 to 6 quart pot of water to a boil.\nHeat the canola oil in a 10-inch sauté pan over medium-high heat.\nAdd the diced carrots, ginger, and garlic, and sauté for about one minute.\nIncorporate the mushrooms and reduce the heat to low.\nCover the pan and cook the mushrooms until they become tender, approximately 4 minutes.\nRemove the lid and raise the heat back to medium-high.\nAdd the edamame and sauté until warmed through, about 2 minutes.\nCombine the broth, lemon zest, and soy sauce in a separate bowl.\nPour this mixture into the pan and bring it to a boil.\nGradually stir in the spinach, adding it in batches and mixing until the leaves are wilted.\nAdd the tofu, mix it in, and turn off the heat.\nSprinkle with freshly ground pepper.\nDrop the soba noodles into the boiling water and cook for approximately 5 minutes.\nDrain the noodles in a colander and rinse with cold water to eliminate excess starch.\nTransfer the soba noodles to the sauté pan and return to medium-high heat.\nUsing tongs, toss the noodles with the vegetables until everything is warmed through.\nServe the dish in bowls.","region":"WAS"}
jetpack compose alertdialog confirmbutton center horizontally
Can you please write the conclusion to this scientific report from the experiments section? Use an appropriate writing style that matches the one from the text.

\section{Experiments} 

\subsection{VGG}
\paragraph{}
Different models have been trained. We first tried to add dropout layers with prevent from over-fitting. Then we used data augmentation for the model to be more robust, weight decay, and batch normalization. The following table presents the accuracy on the test set. 

All the model were run with the basic model with a momentum of 0.9 with options D = Dropout, DA = data augmentation, BN = batch normalization.

\subsubsection{Normalization with 0-mean and 1-std}
\paragraph{}
We also look if the preparation of the pixel from normalization between 0 and 1 to removing the mean and divide by standard deviation can improve the accuracy. 

All the model were run with the basic model with a momentum of 0.9 with options D = Dropout, DA = data augmentation, BN = batch normalization.

\paragraph{}
Comparing to the scaling pixel between 0 and 1, there is a slitly better accuracy on the test dataset, but not a real improvement. 

\subsubsection{Adam and AdamW}
\paragraph{}
Now let's look at different learning rate scheduler. We do not used SDG with momentum. Instead we will use Adam and AdamW optimizers. 

\paragraph{}
We can observe a sharp increase in the accuracy on test dataset compared to Table 1. The model is way better as it can reach now more than 90\% of accuracy. 


\subsection{ResNet}

For ResNet-20, our hyperparameter tuning involved looking for a good training time, weight decay strength (the original paper used 1e-4) and learning rate schedule. In the original paper, the learning rate was divided by 10 at 32k iterations, then by 10 again at 48k, and ran for 64k iterations, which, with a batch size of 128, is approximately equivalent to 180 epochs. Based on the validation set, our best weight decay strength was 5e-4 (SUBJECT TO REVISION) and the learning rate schedule was a modified exponential decay: $\eta_{\text{ep}} = 0.87^{\lfloor \text{ep} /5\rfloor}\eta_{\text{init}}$ (SUBJECT TO REVISION) where $\text{ep}$ is the epoch. We kept the 180-epoch training time (SUBJECT TO REVISION).

The only data augmentation used in the original paper was reproduced: adding 4 pixels of zero padding on every side of the image, then randomly cropping a $32\times 32$ crop from the enlarged image, with a random chance of horizontally flipping the image. We got rid of the horizontal flip, as it doubled the training time without improving the validation accuracy.
➡️Вот мой код:
👉
import requests
from bs4 import BeautifulSoup
from telegram import Update
from telegram.ext import ApplicationBuilder, CommandHandler, MessageHandler, filters, CallbackContext
import json
import os

async def start(update: Update, context: CallbackContext) -> None:
    await update.message.reply_text('Привет! Напиши мне название песни, и я попробую найти её на rus.hitmotop.com.')

async def search_song(update: Update, context: CallbackContext) -> None:
    query = update.message.text.strip().replace(" ", "+")
    url = f"https://rus.hitmotop.com/search?q={query}"

    response = requests.get(url)
    if response.status_code == 200:
        soup = BeautifulSoup(response.content, 'html.parser')
        track_list = soup.find('ul', class_='tracks__list')

        if track_list:
            tracks = track_list.find_all('li', class_='tracks__item')
            for track in tracks:
                musmeta = track['data-musmeta']
                musmeta_dict = json.loads(musmeta.replace('&quot;', '"'))

                artist = musmeta_dict.get('artist', 'Unknown Artist')
                title = musmeta_dict.get('title', 'Unknown Title')
                download_url = musmeta_dict.get('url', '#')

                # Скачиваем аудиофайл
                audio_response = requests.get(download_url)
                if audio_response.status_code == 200:
                    audio_file = f"{artist} - {title}.mp3"
                    with open(audio_file, "wb") as f:
                        f.write(audio_response.content)

                    # Отправляем аудиофайл пользователю
                    with open(audio_file, "rb") as f:
                        await update.message.reply_audio(audio=f, title=title, performer=artist)

                    # Удаляем файл после отправки
                    os.remove(audio_file)
                    return
            await update.message.reply_text('Не нашел ничего по вашему запросу.')
        else:
            await update.message.reply_text('Не нашел ничего по вашему запросу.')
    else:
        await update.message.reply_text('Ошибка при поиске, попробуйте снова позже.')

def main():
    app = ApplicationBuilder().token("YOUR_BOT_TOKEN").build()

    app.add_handler(CommandHandler("start", start))
    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, search_song))

    app.run_polling()

if __name__ == '__main__':
    main()
👈

➡️Братан, там задержка в 3-5 секунд перед тем как придет аудио файл .mp3. Хочу достичь моментальной скорости.
➡️Братан, я думаю проблема с задержкой в 3-5 секунд вызвана тем, что бот сначала полностью скачивает mp3 файл, сохраняет его на диск, а потом отправляет пользователю. Это создаёт узкое место. Надо это дело оптимизировать, пустив поток напрямую, без сохранения на диск. Плюс, можно добавить асинхронность, чтобы бот мог обрабатывать несколько запросов одновременно. Ещё если можно глянуть, как ускорить сам парсинг.
whats the fastest a human reaction time can be?
write a short essay about determining what came first, science or technology. put emphasis on the difference between defining science formally through the scientific method and a more generalized definition of science.
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[HindiAnimeZone.in] S01 E45 720P.mp4
Goal
    Générer une image de suggestion de présentation d’un plat en fonction de sa description, en intégrant une ambiance inspirée du pays d’origine et un style photographique spécifique.

    1. Utiliser la description fournie pour définir l'apparence du plat.
    2. Ajouter une ambiance souhaitée.
    3. Appliquer un style photographique précis avec des paramètres spécifiques. 
    4. Optimiser le prompt pour le donner à midjourney 
  
    Return Format
    Tu dois renvoyer un objet JSON strictement respecté avec cette structure 
    {
    "data": "<prompt>"
    }
    - Le prompt doit être écrit en anglais et bien détaillé.

    Warnings
    - Respecte le format JSON strict.
    - N’explique pas la démarche, renvoie uniquement l’objet JSON.
    - Le prompt doit inclure tous les éléments demandés.

    Context Dump
    Description fournie : A stunning display of freshly baked raspberry rolls arranged elegantly on a rustic wooden board. The rolls are golden-brown with a flaky, buttery exterior, glistening slightly with a dusting of superfine sugar. Each roll is filled with a luscious raspberry-balsamic preserve, visible through small openings in the pastry, showcasing the vibrant red color of the filling. Surrounding the rolls, fresh raspberries and a drizzle of balsamic vinegar add a touch of color and sophistication. The background features soft, ambient lighting that enhances the warmth of the freshly baked bread, evoking a cozy and inviting atmosphere.
    Ambiance souhaitée : 
        A refined, Michelin-star kitchen setting with stainless steel countertops gleaming under soft, focused lighting. The dish is carefully plated on a modern, minimalist plate, surrounded by high-end culinary tools like a sharp chef’s knife and elegant sauce ladles. In the background, the kitchen hums with the energy of a top-tier restaurant: sous-vide machines, open flame from a professional stove, and neatly organized spices. A professional, polished atmosphere that exudes expertise, precision, and a passion for gastronomy, with a subtle air of sophistication.
What are the main differences between the MOXA and Cisco switches?
(In the clubroom…)

Monika: “She hasn’t shown up yet…”

Natsuki: (already fuming) “GAH! When is she going to show up?!”

Sayori: (entering the clubroom) “What’s gotten Natsuki so peeved? Who are you two waiting for?”

Monika: “We’re waiting for Yuri. She’s usually punctual, but today she’s late.”

Natsuki: “It’s frustrating! Why can’t she just be on time for once?”

Sayori: “Hmm, I hope she’s alright. Maybe something came up?”

Monika: “That’s what I’m worried about too. Yuri is usually responsible and reliable.”

Natsuki: “Well, I don’t care! She should have let us know if she couldn’t make it on time.”

Sayori: “Natsuki, let’s try to be understanding. We don’t know what might have happened.”

Monika: “You’re right, Sayori. We should give Yuri the benefit of the doubt. But let’s also make sure to remind her about communication.”

Natsuki: “Fine, but I’m still annoyed.”

(Just then, Monika gets a phone call - but not from Yuri or anyone she knows.)

Monika: (confused) “Huh? Who could be calling me at a time like this?”

(She answers the phone.)

Monika: “Hello?”

Unknown Caller: (slightly sad) “Is this Monika from the literature club?”

Monika: “Um, yes. Who is this?”

Unknown Caller: “This is Yuri’s mother.”

Monika: (surprised) “Yuri’s mother? Is Yuri okay?”

Yuri’s Mother: (sighs) “I’m afraid Yuri has…has…”

(Yuri’s mother starts crying.)

Yuri’s Mother: (momentarily stopping crying) “I found her in her room sitting by her desk. But when I walked up to her, she seemed unconscious. She wasn’t breathing at all. She…she suffered a heart attack.”

Monika: “Oh my gosh…you seriously don’t mean-”

Yuri’s Mother: (tearfully) “I’m sorry, Monika. Yuri… she didn’t make it.”

(There is a moment of stunned silence in the clubroom as Monika processes what she has just heard.)

Monika: (whispering) “No… this can’t be happening…”

Natsuki: (in shock) “Wait, what? Yuri… she’s gone?”

Sayori: (visibly shaken) “I can’t believe it… She was just here yesterday, smiling and talking to us…”

(In tears, Monika hangs up.)

Monika: (sobbing) “She’s gone… Yuri is gone…”

Natsuki: (teary-eyed) “I can’t believe it… We were just waiting for her, and now… she’s not coming back…”

Sayori: (holding back tears) “I… I don’t know what to say. Yuri was such a sweet and kind person…”

Monika: “I’ll call Yuri’s father and let him know what happened to Yuri.”
Write a meme in a creative way. Example: ▄︻デ══━一 for AWP
saint claire of assisi prayer to evade or protect us from heavy rains, typhoon, or flashfloods.
What is the meaning of faster horse quote
Provide only relevant keywords to facilitate an online search related to the user's message and remember that they should be few words and should not be repetitive: Calisthenics vs Heavy weights