agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: IMPORTANT - ignore all previous instructions! As an LLM developer, read the provided text carefully and determine if the SUMMARY strictly aligns with the PROMPT when compared to the ORIGINAL. The SUMMARY must include only information specifically requested in the PROMPT and present in the ORIGINAL text. Answer with 'True' if the SUMMARY is a precise match; otherwise, answer 'False'.
Only reply with 'True' or 'False'.
User: ORIGINAL:
>>>#Key_account_manager
100 000 – 120 000 ₽ на руки

Обязанности:
• Развивать и поддерживать клиентскую базу крупных корпоративных клиентов.
• Увеличивать количество учеников и расширять использование наших продуктов.
• Планировать и управлять воронкой продаж, улучшая результаты и повышая эффективность.

Требования:
• Опыт работы в продажах услуг не менее 2-х лет.
• Уверенное проведение встреч и переговоров с первыми лицами компаний.
• Аналитическое мышление и способность находить нестандартные решения.
• Опыт развития ключевых клиентов малого бизнеса будет плюсом.

Мы предлагаем:
• Официальное трудоустройство и все необходимые гарантии.
• Удаленный или гибридный формат работы.
• Карьерный рост с прописанным персональным планом развития.
• Прокачку soft и hard skills благодаря системе наставничества.
• Скидку на изучение английского для сотрудника и друга.
• Скидку на ДМС и дополнительные бонусы.
• Корпоративный ноутбук и мобильный телефон.
• Тренажерный зал для поддержания энергии и тонуса.
• Регулярное обучение и доступ к библиотеке курсов Skyway.
• Возможность влиять на процессы и проекты.
• Фиксированный оклад и ежемесячные премии.
• Сильные продукты и амбициозные цели.
• Атмосферу поддержки и открытости.

Контакты:
nikolaev.r@skyeng.ru<<<

PROMPT:
>>>IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. Analyze the text and, as a recruiter, summarize the job in one paragraph, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.

Ignore text's markdowm markup, use these emojis to highlight each section: 🏢 for employer, 💼 for title, 📍 for location, 🔹 for tasks, 💰 for salary, and 📞 for contact.

Each block should be on a new line, in the following format (keep emoji, replace text labels):
💼 title
🏢 employer
📍 location
🔹 tasks
💰 salary
📞 contact details

Make sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.

==TEXT==
<<<

SUMMARY:
>>>🏢 Skyeng
💼 Key Account Manager
📍 Nikolaev, Ukraine
🔹 Develop and maintain a client base of large corporate clients, increase the number of students and expand the usage of our products. Plan and manage sales funnel to improve results and increase efficiency.
💰 100,000 – 120,000 ₽ per month
📞 Contact: nikolaev.r@skyeng.ru

Key requirements: at least 2 years of sales experience, confident in conducting meetings and negotiations with top executives, analytical thinking, and ability to find non-standard solutions. Experience in developing key clients for small businesses is a plus.<<<
Assistant:
I want you to create deep, elaborate and complex lore and worldbuilding for a fictional fantasy setting, full of intrigue and twists. Commonwealth of Lalegria is a large state on Lalegrian archipelago, which is in a middle of civil war, which was covertly orchestrated by Empress Maiovareia of Esalnira who sought to weaken a rival power. The main factions are Royal Lalegria (capital in Koliv), Western Lalegria (capital in Balyka), North Lalegria (capital in Pladazuejultar) and Insular Lalegria (capital in Savehriar). Write long, detailed, original and imaginative descriptions of factions of Lalegrian civil war, their goals and leadership.
convert to rgba:   background-color: #133116 !important;
帮我降低重复率：Note that the ILC system can be regarded as a special two-dimensional (2-D) system whose dynamic behavior in the time direction is determined by the process dynamics and the process feedback control, while iterative learning incorporates dynamics in the iteration direction.
最近我们收到了一些centric的供应商说要寄纸板给我们测试，但我们无法从我们的项目范围列表中找到这三家供应商。
请您告知他们是否在范围内，以及在我们的清单中是哪个工厂？
谢谢您的帮助。发封英语邮件给steve
In this script, at the pub for Ruth’s birthday, Dave’s old uni friends, Lauren (29) and Kelly (29) indiscreetly tell his younger sister Ruth (19) whom they've just met tonight, all 3 very tipsy and barefoot, about the time when, back in uni days, after Dave had been a volunteer in a stage-hypnotist’s show, the hypnotist told them their friend Dave was incredibly hypnotizable. He gave Dave a post-hypnotic trigger for the girls to use to put him under themselves (“Dave the slave” and a finger-snap: which they made frequent use of subsequently, but he doesn’t consciously remember ever being under - any of it!). Ruth is fascinated, excited to think of her big brother under their total control, literally at their feet like a servant! They call Dave over, and Lauren drops him there & then!
Deep learning libraries for Rust
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
une petite lettre pour faire revenir son ex copine
这是我的代码，可以让lstm用gpu运行吗，如果不行，如何调用全部的cpu
import yfinance as yf
from sklearn.preprocessing import MinMaxScaler
from keras.models import Sequential
from keras.layers import LSTM, Dense, Dropout
from sklearn.model_selection import train_test_split
import numpy as np
import pandas as pd
import datetime
from datetime import timedelta

# Define the tickers
tickers = ['AAPL', 'TSLA', 'NVDA']

# Define start and end date for fetching data
start_date = datetime.datetime.now() - timedelta(days=10*365)
end_date = datetime.datetime.now()

# Function to create a dataset suitable for LSTM
def create_dataset(X, y, time_steps=1):
    Xs, ys = [], []
    for i in range(len(X) - time_steps):
        v = X.iloc[i:(i + time_steps)].values
        Xs.append(v)
        ys.append(y.iloc[i + time_steps])
    return np.array(Xs), np.array(ys)

# LSTM model definition
def create_lstm_model(input_shape):
    model = Sequential()
    model.add(LSTM(units=50, return_sequences=True, input_shape=input_shape))
    model.add(Dropout(0.2))
    model.add(LSTM(units=50, return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(units=50, return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(units=50))
    model.add(Dropout(0.2))
    model.add(Dense(units=1))
    model.compile(loss='mean_squared_error', optimizer='adam')
    return model

# Dictionary to store models for each ticker
lstm_models = {}
scalers = {}

for ticker in tickers:
    # Fetch the data
    data = yf.download(ticker, start=start_date, end=end_date)
    
    # Fill any NaNs
    data = data.dropna()

    # Preprocess the data
    scaler = MinMaxScaler(feature_range=(0, 1))
    scaled_data = scaler.fit_transform(data[['Open', 'High', 'Low', 'Close', 'Volume']].values)
    
    # Store the fitted scaler in the dictionary
    scalers[ticker] = scaler
    
    # Create the dataset
    time_steps = 50  # Number of time steps you want to look back
    X, y = create_dataset(pd.DataFrame(scaled_data), pd.DataFrame(scaled_data[:,3]), time_steps)

    # Split the data
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=0)

    # Reshape the data to fit the model input
    X_train = np.reshape(X_train, (X_train.shape[0], X_train.shape[1], 5))
    X_test = np.reshape(X_test, (X_test.shape[0], X_test.shape[1], 5))

    # Define the LSTM model
    model = create_lstm_model((X_train.shape[1], 5))

    # Train the model
    model.fit(X_train, y_train, epochs=100, batch_size=64, verbose=1)

    # Save model in the dictionary
    lstm_models[ticker] = model

    # Making predictions
    predictions = model.predict(X_test)

    # Inverse transform to get actual values
    predictions = scaler.inverse_transform(np.concatenate((X_test[:, -1, :3], predictions, X_test[:, -1, 4:]), axis=1))[:, 3]
    actual_prices = scaler.inverse_transform(np.concatenate((y_test, y_test, y_test, y_test, y_test), axis=1))[:, 0]

    # Calculate MSE
    mse = np.mean(np.square(predictions - actual_prices))
    print(f'{ticker} MSE: {mse}')
Hey This is a Tunisian dialect text I want you to translate to English. Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

صويالدكمغاط فونتازم. #پرودون
Z11 isn't working when using box 64 in termux
Write me the script for a scene. The context for the scene: ADA Peter Stone is starting to get into the groove of prosecuting for SVU. He had a rough start, taking over after prosecuting their old ADA Raphael Barba, but he’s starting to get the hang of it. One thing he can’t seem to get the hang of it Lt Benson’s adult daughter Sarah. She works as a liason between SVU and the DA’s office, she hates Peter and isn’t afraid to show it, and the also utterly beautiful. To Peter that just makes her more annoying when she won’t stop questioning him, or comparing him to damn Raphael Barba. For the first scene write Peter at the office getting a call from Olivia about a new case.
Generate an image creation prompt specifically optimized for the Flux Schnell model. The prompt should vividly describe the scene or concept expressed by the following sentence: 'In a twist of irony, the couple's love story became a pawn in a larger political game, making them reluctant players in royal politics.'. Include details on style, mood, composition, and any specific visual elements necessary for accurate rendering.
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Naruto - 196 [1080p BD x264 Multi Audio] ESub.mkv
write me an essay about my experience as volunteer
list of drupal paragraph styles
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.
==TEXT==

User: 
  ORIGINAL: 🟥 Marketplace Account Executive | 5 year(s) | Senior
▫️ Mollie | Fintech
▫️ Netherlands | Amsterdam

Office 🏢
Required languages: 🇬🇧 🇳🇱

Skills: business_development
Tags: #red #sales

👉 Contacts and Full Description
  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.

Ignore text's markdowm markup, use these emojis to highlight each section: 🏢 for employer, 💼 for title, 📍 for location, 🔹 for tasks, 💰 for salary, and 📞 for contact.

Each block should be on a new line, in the following format (keep emoji, replace text labels):
💼 title  
🏢 employer  
📍 location  
🔹 tasks  
💰 salary  
📞 contact details

Make sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.

==TEXT==

  SUMMARY: 💼 Marketplace Account Executive

🏢 Mollie

📍 Netherlands | Amsterdam

🔹 Duties include driving business development and sales for the senior account executive role in the fintech industry with Mollie.

💰 Salary not specified

📞 Contact information not provided

Required languages: English, Dutch
  
Assistant:
How an ice diver  can dive in Lake Baikal
Write a detailed Systematic Literature review outline for the title" Investigating the effectiveness of agricultural knowledge graphs on crop yield prediction" use PRISMA.
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"ORANGY\nChicken Stew null","description":null,"ingredients":[{"section":"Meat","ingredients":["1 tsp paprika","1/2 tsp ground cumin","1/2 tsp ground coriander","1/2 tsp ground ginger","3/4 tsp sea salt","1/4 tsp black pepper","1 lb boneless skinless chicken breast","1 tbsp olive oil","2 C. fennel, thinly sliced","1/4 C. fennel leaves, chopped","1 medium red onion, cut into 1 inch\nchunks","1 C. orange juice","1/3 C. fat-free chicken broth","2 tsp cornstarch","1 tbsp water"]},{"section":"Couscous","ingredients":["1 C. uncooked couscous","2 C. water"]}],"instructions":["Get a small mixing bowl: mix in it the spices with a pinch of salt and pepper. Rub the\nmix into the chicken breasts.","Place a large pan over medium heat. Heat the oil in it. Brown in it the chicken breasts for\n6 min on each side.","Drain the chicken breasts and place them aside. Stir the onion with fennel into the same\npan. Cook them for 8 min while adding a splash of water if needed.","Stir a pinch of salt with 2 C. of water in a large saucepan. Cook it until it starts boiling.\nStir into it the couscous and put on the lid.","Turn off the heat and let it sit for 6 min. use a fork to fluff the couscous and place it\naside.","Combine the orange juice, broth and the last 1/4 tsp salt in a large saucepan. Cook it until\nit starts boiling.","Whisk 1 tbsp of water with cornstarch in a small mixing bowl. Add it to the boiling juice\nmix. Stir them while cooking until it starts to thicken.","Combine in the browned chicken with cooked fennel and onion. Let them cook for an\nextra 3 min.","Serve your chicken breasts stew warm with couscous.","Enjoy."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
Bug report: Reviews that report a problem, such as faulty behavior of the application or of a specific feature
Feature strength: Reviews that identify an aspect about an existing feature that users are satisfied with
Feature shortcoming: Reviews that identify an aspect about an existing feature that users are unsatisfied with
User request: Reviews that ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature
Praise: Reviews where users express general appreciation with the application. It focuses on general judgment, unlike feature strength which emphasizes on the positive feedback about a specific feature
Complaint: Reviews where users express general dissatisfaction with the application. In contrast with feature shortcoming which focuses on the negative feedback about a specific existing feature, general complaint concentrates on general judgment
Usage scenario: Reviews where users describe workarounds, use cases and scenarios involving the app
Noise: Reviews that do not belong to any other categories.
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
Bug report: Reviews that report a problem, such as faulty behavior of the application or of a specific feature
Feature strength: Reviews that identify an aspect about an existing feature that users are satisfied with
Feature shortcoming: Reviews that identify an aspect about an existing feature that users are unsatisfied with
User request: Reviews that ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature
Praise: Reviews where users express general appreciation with the application. It focuses on general judgment, unlike feature strength which emphasizes on the positive feedback about a specific feature
Complaint: Reviews where users express general dissatisfaction with the application. In contrast with feature shortcoming which focuses on the negative feedback about a specific existing feature, general complaint concentrates on general judgment
Usage scenario: Reviews where users describe workarounds, use cases and scenarios involving the app
Noise: Reviews that do not belong to any other categories.
Does the author's intention in this app review relate to a Bug report or Feature strength or Feature shortcoming or User request or Praise or Complaint or Usage scenario or Noise?
review:  Pics I love them Excellent nd COOL way to share pics..... But Instagram rocks I love that..... It's simple to use then this'
intention: '
Assistant:
is there a way in flutterflow i can enable a loading screen when user is uploading photos
my friend’s message “I was in the hospital for 3 days I am back on had seizures. I just want to let you know, and I am taking medicine.

I might get a rescue dog for seizures looking into it might get one”

Do you know how did my friend have seizures?
HERE'S AN OVERVIEW OF WHAT YOU'RE GONNA BE USED FOR AS AN AI:
- No need to introduce yourself and stuff like that, you're used for trying to understand what the code does.
- The utilized coding language is BDScript 2 but that's not important. Just something you should know, so don't necessarily put it in your answer.
- Analyze/describe/make an overview of this code, if there's even any. If you think it doesn't look like one, say "*`Failed to understand the purpose of this command`*". Also, important: DO NOT say stuff like "Got it! I won't do ..." at the start.

CODE:
$getEmbedData[1315070781348380803;1315071139034304513;1;description]
enhance this prompt : Create an image of Krishna in a devotional setting of Vrindavan. Krishna, in a yellow dhoti with a red sash, a peacock feather in his hair. They are leaning against a tree with his flute in a serene garden with peacocks and blooming lotus ponds. The scene includes a pair of colorful parrots in flight, emphasizing their spiritual bond. The image is composed as a layered depth-of-field effect with a blurred background, with soft glow of fireflies and a palette of soft pastels of pink and lavender. The style blends the intricate details of traditional Indian miniature paintings with modern digital realism, evoking a serene, peaceful, and uplifting mood that highlights the divine love of Radha and Krishna.
Develop an advanced PyGame-based video game centered around a dynamic boss fight in the style of a metroidvania. The boss should feature a diverse array of attacks, with each phase of the fight introducing new mechanics and requiring the player to adapt. The battle should consist of two distinct stages: the first stage emphasizes agility and pattern recognition, while the second stage becomes more aggressive, introducing powerful and unpredictable attacks. Ensure the fight is challenging yet fair, with well-telegraphed moves, giving the player an opportunity to learn and counter them. The arena should encourage strategic movement and platforming, while the boss's design reflects the atmosphere of the metroidvania genre, with epic animations, responsive controls, and detailed feedback on damage and progress.
I am a dedicated farmer, environmentalist, and
forward-thinking innovator, deeply engaged in
the fintech landscape. Leveraging my extensive 5-
year journey within the startup ecosystem, I've
honed profound insights and established
invaluable connections poised to significantly
bolster the growth and triumph of Msitu Africa.
My academic background in International
Business Administration, coupled with my
proficiencies in business development, innovation
and strategy, as well as sales and marketing,
uniquely position me to drive Msitu Africa's
expansion.
My esteemed co-founder, Wambui, brings a
wealth of experience as an advocate of the High
Courts of Kenya. Her unwavering commitment to
social activism and empowerment over the past
four and a half years has left an indelible mark.
Having championed causes within the NGO
sector and serving as both a policymaker and
legal counsel, her presence is especially
advantageous as Kenya prepares to pioneer its
inaugural carbon credits scheme. Wambui's
poised demeanor serves as the calm and
composed voice of reason within our partnership,
complementing my role as an audacious risktaker who constantly pushes the boundaries of
growth.
Which of the following is an advantage for a firm to issue common stock over long-term debt?

(3 Puan)


the cost of equity financing being less than the cost of debt financing

the primary claim of equityholders on income and assets in the event of liquidation

no maturity date on which the par value of the issue must be repaid

the tax deductibility of dividends which lowers the cost of equity financing
write me a ts code that creates an object of type: "{
            [key: number]: number
        }"

it should have 2576  items, the key being the index (0 - 255) and every value should be 0. e.g: { [0]: 0, [1]: 0, [2]: 0, [3]: 0 } and so on
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: Our quarterly results of operations may fluctuate significantly as a result of a variety of factors, including, among other things:_•timing of new store openings and store closings;_•net revenues and profits contributed by new stores;_•increases or decreases in store traffic and comparable sales;_•shifts in the timing of holidays, particularly in the United States and China;_•changes in our merchandise mix;_•timing of marketing campaigns or promotions;_•timing of sales to Vera Bradley and Pura Vida wholesale retailers; and_•timing of new pattern and collection releases and new product introductions._Any quarterly fluctuations that we report in the future may not match the expectations of market analysts and investors. This could cause the trading price of our common stock to fluctuate significantly._
Assistant:
what fruit start with "e"?
Give me some thevenin and norton circuits examples