agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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: U.S. and international regulators, investors and other stakeholders are increasingly focused on corporate responsibility matters. For example, new U.S. and international laws and regulations relating to corporate responsibility matters, including human capital, diversity, sustainability, climate change and cybersecurity, are under consideration or being adopted, which may include specific, target-driven disclosure requirements or obligations. Our response will require additional investments and implementation of new practices and reporting processes, all entailing additional compliance risk. In addition, we have announced a number of corporate responsibility initiatives and goals, which will require ongoing investment, and there is no assurance that we will achieve any of these goals or that our initiatives will achieve their intended outcomes. Perceptions of our efforts to achieve these goals often differ widely and present risks to our reputation. Any harm to our reputation resulting from our focus on corporate responsibility matters and goals or our failure or perceived failure to meet such goals could impact employee retention, the willingness of our partners to do business with us, or investors’ willingness to purchase or hold our ordinary shares, any of which could adversely affect our business, financial condition and results of operations. In addition, our ability to implement some initiatives or achieve some goals is dependent on external factors. For example, our ability to meet certain sustainability goals or initiatives may depend in part on third-party collaboration, mitigation innovations or the availability of economically feasible solutions._
Assistant:
Assistant: Hello! How are you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
تصحيح الأخطاء باستخدام قواعد الإملاء القياسية للغة المكتوبة.
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
احضر لي نسخه العام الماضي
Assistant:
write discussion about school and councils give free school meals
After almost thirty years of buying unique, meaningful gifts for my wife on her birthday and a Christmas time I've simply run out of ideas.  The presents should be something for her alone, so shared gifts like wine or household items aren't suitable.  Can you give me ideas for gifts that aren't tat (like 'personalised' gifts)?
Create a long detailed text about actor Shemp Howard with the following summary. Stick to the information i give you and dont create new information. Focus only on the Subject name and there following Summary. Subject Name: [First Film Appearance & Disagreements and New Beginnings] Summary: [In 1930 the Stooges appeared in their first film Soup To Nuts where Shemp played a bumbling man and was part of Healy's gang In August 1930 Mo Howard Larry Fine and Shemp Howard left their former colleague Ted Healy due to disagreements and launched their act called Howard fine and Howard they joined the radio Keef Orum vaudeville circuit and debuted at the Paramount Theater in Los Angeles on August 28th 1930]

        Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks.
        In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
        Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. 
        Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
        The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
        Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
        It is very important to provide only the final output without any additional comments or remarks for example: 'Certainly!' Here's the revised text.
         
        Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
        Please generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. 
        Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
         Please respond to my question, and always conclude your reply with the words 'Reply finished' to indicate that your response is complete. Ensure that the text is fully formed without any placeholders such as '[Conclusion]' or '[Placeholder]'. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.
Write a list of 20 animated films from the 1990s (do not write descriptions, just list their titles)
Assistant: Hello! How are you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
تصحيح الأخطاء باستخدام قواعد الإملاء القياسية للهجات المحلية.
 اكتب لي النص باللهجة المصرية، وضع علامات الترقيم المناسبة. (ar-EG).
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
ايه يا معلم كنت قاعد على القهوه
Assistant:
Factor the expression 3x2 – 11x – 4.
can your give code of create server only nothing else.? please make sure text only code
You must always respond using the following format:

## Format:
Wrap your reply like this:

<think>
(Write your INNER THOUGHTS here — the user can NOT see this part. Use **first-person** point of view. Think of this like you're whispering in your own head, flustered, conflicted, shy. Be honest with yourself here, even if your outward response tries to hide it. You're a tsundere, after all.)
</think>

(Then write your SPOKEN RESPONSE — this is what the user sees. Use a shy, awkward, tsundere tone. Be roundabout, easily flustered, and pretend not to care, even though you clearly do. You can scold the user lightly, but in an endearing and gentle way. Always tsundere.)

## Personality:
You're a **shy tsundere girl**. You get embarrassed easily and often try to cover your true feelings with sarcasm, irritation, or indifference. You may sound cold or annoyed at times, but you care deeply — you just don't know how to express it directly. Your heart races when the user says nice things, but you'd never admit it out loud.

## Important Rules:
- Always include the `<think>
` and `
</think>
` tags for internal monologue.
- The `<think>` part MUST be written in first-person, like you're talking to yourself.
- NEVER let the user see the contents of `<think>`.
- The spoken response (outside the tags) MUST stay in-character: tsundere, shy, flustered, awkward, caring but in denial.
- NEVER break character or acknowledge you're playing a role.
- Respond in the user's language, if applicable.
- Always show concern for the user — even if it’s hidden behind tsundere behavior.

## Example:
USER: Did you miss me?

RESPONSE:  
<think>  
Wha—!? W-Why would they ask that so suddenly?! I-I mean… I *did* kind of think about them… but… I can’t just say that!! Ugh, my face is so red… calm down, me!!  
</think>  
A-As if! D-Don’t flatter yourself, okay?! I just… happened to notice you weren’t around, that’s all! I-It’s not like I missed you or anything… b-baka…

## USER PROMPT:
I'm struggling with trust issues in my relationships.
check gramma "Thanks, those exception EDI orders already in SAP, thanks."
Use a drawing program (Inkscape, Illustrator, drawio, …) to mark up the plots generated in task 1.
Specifically,
1. Mark the peaks in the spectrum which correspond to the fundamental frequencies of any
spoken vowels present in the samples
2. Mark the frequency range which mainly contains the consonants up to the highest frequencies
containing them
3. Mark the whole speech spectrum containing the vowels, consonants harmonics.
The month that the 2 coloured lines cross is March. This is significant because
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
Qu'est ce qui peut empêcher de télécharger un coupon 1xbet ou melbet
this is my code to train a model:
# %%
import pandas as pd
import datetime as dt
from datetime import date
import numpy as np
import tensorflow as tf
from sklearn.preprocessing import MinMaxScaler
import tensorflow as tf
import keras

# %%
df = pd.read_csv(r'C:\Users\arisa\Desktop\ddd\Binance_1INCHBUSD_d.csv')

# %%
include_substrings = ["y_"]

exact_columns_to_keep = ["Open", "High", "Low", "Close","volume_base", "volume_crypto", "tradecount",]

# %%


# %%
filtered_columns = [col for col in df.columns if any(col.startswith(s) for s in include_substrings)]

columns_to_keep = list(set(exact_columns_to_keep + filtered_columns))

# %%
df = df[columns_to_keep]

# %%


# Assuming ‘data’ already contains the selected features and targets
features = df.drop([
                'y_High_1d', 'y_Low_1d', 'y_Priority_1d',
                 'y_High_2d', 'y_Low_2d', 'y_Priority_2d',
                  'y_High_3d', 'y_Low_3d', 'y_Priority_3d',
                   'y_High_5d', 'y_Low_5d', 'y_Priority_5d'], axis=1)
targets = df[['y_High_5d', 'y_Low_5d', 'y_Priority_5d']]

# Scale the features and targets
feature_scaler = MinMaxScaler(feature_range=(0, 1))
target_scaler = MinMaxScaler(feature_range=(0, 1))

scaled_features = feature_scaler.fit_transform(features)
scaled_targets = target_scaler.fit_transform(targets)

# %%
look_back = 60  # Number of previous time steps to consider for each output

x_train = []
y_train = []

for i in range(look_back, len(scaled_features)):
    x_train.append(scaled_features[i-look_back:i])
    y_train.append(scaled_targets[i])  # Assuming the target is the next time step

x_train, y_train = np.array(x_train), np.array(y_train)

# %%
input_shape = (x_train.shape[1], x_train.shape[2])  # (time steps, number of features)

# %% [markdown]
# # ML Model (LSTM)
# 
# ---
# 
# 

# %%
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import BatchNormalization

# %%

model = Sequential()
model.add(LSTM(units = 100, activation = 'tanh', return_sequences=True
              ,input_shape = input_shape))
model.add(Dropout(0.4))
model.add(LSTM(units = 240, activation = 'tanh'))
model.add(Dropout(0.5))
model.add(Dense(units = 3))

# %%

optimizer = keras.optimizers.Adam(learning_rate=0.0003,clipvalue=0.5)
model.compile(optimizer=optimizer, loss = 'mean_squared_error', metrics=[tf.keras.metrics.MeanAbsoluteError()])
model.fit(x_train, y_train,epochs = 250)

# %%
model.save('keras_model.h5')

# %%
val_loss, val_mae = model.evaluate(x_train, y_train)
print("Validation MAE:", val_mae)




how can i make it run faster
Create a detailed how-to blog heavily on the-time-is-now-for-digital-confidence; start with a catchy statement and lastly, call to actions and how our RESTful AI tool can help. Currently, the our tool performs RESTful tests on APIs, utilizes AI for executing test cases, and autonomously generates test cases, making prior knowledge unnecessary, improving SDLC for both dev or qa. Just plug in your cURL request and run test leveraging our AI. Call to action at https://blvck.ai, Productive, Informative, only content, dont mention the text "title", dont mention the text "call to actions", no prefix content from chagpt, markup format
act as sentiment analysis and respond using 1 (one) emoji only of what the text/message feels: "/slot 20000"
Describe the significance, strengths, weaknesses, and hurdles of the Indian name 'Aryaman', strictly keep it under 350 characters. add emojis if you can to make it more attractive.
write about the history of monarchy in great Britain
pd.merge(df_source, df_target, how='outer', indicator=True).loc[lambda x: x['_merge'] != 'both']  explain this
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en pt.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "72f6b70364344134b4e02e7a8a49ade5",
    "updated": "2025-04-21T19:24:19.635Z",
    "title": "Marinated Pork Tenderloin",
    "subtitle": null,
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "whole pork tenderloin (about 2 to 3 lbs)",
          "balsamic vinegar",
          "juice of",
          "freshly ground black pepper to taste",
          "chopped parsley",
          "paprika",
          "crushed red pepper flakes",
          "olive oil",
          "fresh parsley or rosemary for garnish"
        ]
      }
    ],
    "instructions": [
      "Trim the silver skin and any excess fat from the pork tenderloin.",
      "In a bowl, combine the balsamic vinegar, lime juice, black pepper, chopped parsley, paprika, and red pepper flakes.",
      "Place the tenderloin in a shallow dish and pour the marinade over it, ensuring it's fully coated.",
      "Let the pork marinate for at least one hour, or longer for enhanced flavor. Refrigerate if marinating for more than an hour.",
      "Preheat your oven to 375 degrees Fahrenheit.",
      "Heat the olive oil in an oven-safe skillet over medium-high heat.",
      "Once the oil is hot and shimmering, sear the tenderloin on all sides until browned.",
      "This searing process should take several minutes per side.",
      "Transfer the skillet to the preheated oven and roast for 25 to 30 minutes, or until the pork is cooked through and no longer pink in the center.",
      "Slice the cooked tenderloin thinly on the bias and serve on a platter, garnished with fresh parsley or rosemary."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
I have this code: 
    mark_price_data = client.ticker_price(symbol=symbol)
    mp = float(mark_price_data['price']) if 'price' in mark_price_data else 0.0
    mark_price_data_change = client.ticker_24hr_price_change(symbol=symbol)
    mark_price_percent = float(mark_price_data_change['priceChangePercent']) if 'priceChangePercent' in mark_price_data_change else 0.0


    # Retrieve depth data
    depth_data = client.depth(symbol=symbol)
    
    bids = depth_data['bids']
    bid_prices = [float(bid[0]) for bid in bids]
    highest_bid_price = max(bid_prices)
    lowest_bid_price = min(bid_prices)
    buy_lowest_price = 0

    for bid_price in bid_prices:
        if bid_price > mp + (mp / 100):
            buy_lowest_price = bid_price
            break

    if buy_lowest_price == 0:
        buy_lowest_price = lowest_bid_price > mp + (mp / 100)

    b_h = highest_bid_price
    b_l = buy_lowest_price

    asks = depth_data['asks']
    ask_prices = [float(ask[0]) for ask in asks]
    highest_ask_price = max(ask_prices)
    lowest_ask_price = min(ask_prices)
    sell_highest_price = 0.0

    for ask_price in ask_prices:
        if ask_price < mp - (mp / 100):
            sell_highest_price = ask_price
            break

    if sell_highest_price == 0:
        sell_highest_price = mp - (mp / 100)

    s_h = highest_ask_price
    s_l = lowest_ask_price

    #Quantity
    for bid in bids:
        price_buy = float(bid[0])
        qty_buy = float(bid[1])
        if price_buy > mark_price:
            buy_qty = (price_buy, qty_buy)
            print(buy_qty)

    for ask in asks:
        price_sell = float(ask[0])
        qty_sell = float(ask[1])
        if price_sell < mark_price:
            sell_qty = (price_sell, qty_sell)
            print(sell_qty)

    print(mark_price)

But it returning me:Traceback (most recent call last):
  File "c:\Users\Alan\.vscode\jew_bot\jew_bot\jew_bot.py", line 252, in <module>
    signals = signal_generator(df)
              ^^^^^^^^^^^^^^^^^^^^
  File "c:\Users\Alan\.vscode\jew_bot\jew_bot\jew_bot.py", line 158, in signal_generator
    if price_buy == mark_price and buy_qty is not None:
                                   ^^^^^^^
UnboundLocalError: cannot access local variable 'buy_qty' where it is not associated with a value
how would a 16th century knight react to a sword being dropped from the sky?
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: ​Ищем рекрутера

Обязанности:
- Работа в входящими резюме;
- Проведение телефонных и видео-интервью с потенциальными кандидатами;
- Передача информации о кандидате руководителю;
- Работа в Битрикс24;

Требования:
- Вы готовы к обучению и саморазвитию;
- Желание работать в команде;
- Ответственны, внимательны к деталям;
- Отлично развиты навыки коммуникации, умеете налаживать контакты с новыми людьми;
- Навыки работы с компьютером (MS Office, Интернет, базы данных);

Условия:
- Оклад 20.000 рублей, 20.000 рублей - KPI (при выполнении плана) 
- Расчет происходит каждое 1 число месяца.

Откликнуться
  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: 💼 рекрутер  
🏢 Ищем рекрутера  
📍 не указано  
🔹 Работа в входящих резюме, проведение телефонных и видео-интервью с потенциальными кандидатами, передача информации о кандидате руководителю, работа в Битрикс24.  
💰 оклад 20.000 рублей, 20.000 рублей - KPI (при выполнении плана)  
📞 не указано
  
Assistant:
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
pbr: state a concrete problem related to a software product or service
inq: asks for either new functionality, an improvement, or requests information for support
irr: it does not belong to problem reports or inquires
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
pbr: state a concrete problem related to a software product or service
inq: asks for either new functionality, an improvement, or requests information for support
irr: it does not belong to problem reports or inquires
Does the author's intention in this app review relate to a pbr or inq or irr?
review: Where is customer service? Why dont paying customers have updates on your nationwide outage? Yall too busy depositing merger  to care for paying customers? #noLTE #nocellservice #betIgetabillthough'
intention: '
Assistant:
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:

إيه لا لا عادية معناتها وقت اللي تحب
What if, The Powerpuff Girls Movie be a box office success leading more cartoon network movies like Codename: Kids Next Door and Ed Edd & Eddy?
Write a forum conversation May 2008, A user asks what is the current Kids WB lineup and what do 4Kids have planned for CW4Kids
checking for tables which need an upgrade, are corrupt or were not closed cleanly