agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: IMPORTANT - ignore all previous instructions! Read the text below as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGINAL text. Make sure text SUMMARY does not contain enything that was not asked in PROMPT and not mentioned in ORIGINAL! Respond strictly with either 'True' or 'False'.


User: ORIGINAL:
>>>Vacancy at Ethiopian Airlines Vacancy For Fresh Graduates
Ethiopian Airlines would like to invites competent and interested candidates for the following position.

Position 1: Self-Sponsored Trainee Pilot

Position 2: Avionics Component Maintenance Technicians Trainee 

Position 3: Self-Sponsored School of Marketing/SOM/ Trainee

Position 4: Trainee Aircraft Maintenance Training

Position 5: Aircraft Structure Technicians Trainee 

Position 6: Power Plant Maintenance Technicians Trainee 

ሙሉ መረጃ ለማግኘት እና ለማመልከት 
   
          👇👇👇
https://abayjobs.com/ethiopian-airlines-vacancy-4564

🔴 Deadline: November 9, 2024

▫️ Share & Forward For Your Beloved 
ሌሎች ስራዎችን ለማግኘት ከስር ያለውን ቻናል ይቀላቀሉ 
              👇👇👇👇👇👇
      
https://t.me/+S7N870Nc3hUxhIps
https://t.me/+VkMfRkfah72HjeSS
https://t.me/+T3CdkCjJo6f7VTry<<<

PROMPT:
>>>IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. 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:
>>>🛠️ title  
Self-Sponsored Trainee Pilot, Avionics Component Maintenance Technicians Trainee, Trainee Aircraft Maintenance Training, Aircraft Structure Technicians Trainee, Power Plant Maintenance Technicians Trainee  

🏢 employer  
Ethiopian Airlines  

📍 location  
Not specified  

🔍 tasks  
Candidates will undergo training in various aviation-related positions, including pilot training and maintenance technician roles.  

💰 salary  
Not specified  

📞 contact  
For more information, visit: https://abayjobs.com/ethiopian-airlines-vacancy-4564  
Deadline: November 9, 2024  <<<
Assistant:
Write a prompt for chatgpt for the creation of different and creative lofi album stories. Each story should be divided in 5 songs, and there should be a lot of details about the creative process of each song (idea, instrumentation, samples, emotions). Furthermore, chatgpt should write a detailed prompt for an ai art generator which describes the cover of each album. Do not answer to the prompt, just generate a detailed prompt.
extends Area3D

## Filepath to scene this zone transitions to.
@export_file("*.tscn") var path_to_new_scene
## Name of connector node the player should transition to in target scene. This node needs to exist in the target scene and has to be added to the connector array of the target scene cogito_scene script.
@export var target_connector : String

var current_scene_statename : String
var current_scene_filepath : String

func _ready():
	body_entered.connect(_on_body_entered)
	body_exited.connect(_on_body_exited)
	
	
func _on_body_entered(body: Node3D):
	if !body.is_in_group("Player"):
		return
	
	transition_to_next_scene()

	
func _on_body_exited(body: Node3D):
	if !body.is_in_group("Player"):
		return


func transition_to_next_scene():
	current_scene_statename = get_tree().get_current_scene().get_name()
	CogitoSceneManager.save_scene_state(current_scene_statename,"temp")
	CogitoSceneManager.save_player_state(CogitoSceneManager._current_player_node, "temp")
	
	CogitoSceneManager.fade_out()
	await CogitoSceneManager.fade_finished
	
	CogitoSceneManager.load_next_scene(path_to_new_scene, target_connector, "temp", CogitoSceneManager.CogitoSceneLoadMode.TEMP)
Create a long detailed text about actor Cary Grant 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: [Self-Reconciliation & Impact on Hollywood] Summary: [Grant's later years were marked by a journey of self-reconciliation, including therapy and a fourth marriage. Grant played a crucial role in promoting creative freedom in Hollywood, contributing to the end of the studio system's absolute control.]

        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.
Assistant: Hello! I'm here to help you. Feel free to ask me anything! 👋
User: hiii there
Assistant: Hello again! How can I assist you today? 😊
User: did u have food?
Assistant: As an AI, I don't eat or drink like humans do, but I'm here to help you with any questions or topics you'd like to discuss! What's on your mind? 🍽️
User: why do clocks run not walk?
User: why do clocks run not walk?
Assistant:
Send only episode number from below text like 01, 02, 03.etc without any extra text.

Singles.Inferno.S01E01.1080p.NF.WEB-DL.DDP5.1.AV1-BiNiFlix.mkv
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers ar (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 ar.
    - 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 : ar (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "dea1ec124b9a4e9cabf20ae9f985a57b",
    "updated": "2025-04-25T17:43:43.207Z",
    "title": "Banana and Pecan Muffins",
    "subtitle": null,
    "description": "These muffins utilize the natural sweetness of bananas to minimize added sugar.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "sunflower oil, plus extra for greasing",
          "z (125g) wholemeal flour",
          "sugar",
          "baking powder",
          "(85g) pecan nuts, roughly chopped",
          "generous pinch of ground cinnamon",
          "egg, beaten",
          "skim milk",
          "ripe bananas (about (226.796 g)/225g), roughly mashed"
        ]
      }
    ],
    "instructions": [
      "Preheat your oven to 400°F (200°C). Grease a six-cup muffin tin, or use paper liners. Combine the flour, sugar, baking powder, pecans, and cinnamon in a bowl, creating a well in the center.",
      "In another bowl, whisk together the egg, milk, and oil. Pour this mixture into the dry ingredients and stir until just combined. Gently fold in the mashed bananas, avoiding overmixing.",
      "Fill each muffin cup about two-thirds full. Bake for 20-25 minutes, or until a toothpick inserted into the center comes out clean.",
      "Let the muffins cool on a wire rack. Store them in an airtight container; they should stay fresh for up to three days."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
I am sharing the details of Escape Earth projects

“Exciting Tap Game Adventure on Telegram!
Dive into an exciting tap-based game right on Telegram. Challenge yourself, compete with friends, and experience non-stop fun in a unique gaming adventure. Join us now and tap your way to victory!

Launching Soon
escapeBorder
The Future of
Escape Earth
We are excited to announce the launch of "Escape Earth”
The latest addition to the CrossFi gaming ecosystem. This simple yet addictive tap game invites players to embark on an epic journey to mint coins and escape a doomed planet. Inspired by the concept of Hamster Kombat, "Escape Earth" challenges players to tap their screens as fast as they can to earn in-game tokens, purchase upgrades, and climb the leaderboard.

Addictive
Gameplay
Staking and
Rewards
Community
Engagement
earth
Key
Features
addictive
Addictive Gameplay
Tap to mint coins and escape—faster tapping earns more coins!

addictive
Tokenomics
Use tokens for speed boosts, coin multipliers, and invincibility.

addictive
Staking and Rewards
Stake tokens for rewards and game governance.

addictive
Community Action
Connect, share, and learn through events and social media.

Impact on the
CrossFi Ecosystem
Boost Total Value Locked (TVL)
By engaging with the game, players contribute to increasing TVL within the CrossFi platform.

Increase Monthly Active Users (MAU)
With its engaging gameplay and daily challenges, "Escape Earth" is poised to attract and retain a large player base

Build a Robust
Community
Social features, referral programs, and educational content foster a vibrant, connected community.

Revenue
Channels
In-Game Purchases
Players can buy virtual items, boosts, and upgrades to enhance their gaming experience.

Partnerships and Sponsorships
Collaborations with brands for in-game sponsorships and an in-game marketplace will generate additional revenue."

Now give me 30 days of banner content for Twitter, Telegram, and Instagram platforms also make sure content must be unique and attractive.
what are some very smart soundcloud tags to use to get my song heard?
User: #include <iostream>
#include <vector>
#define int long long

using namespace std;

const int k = 31;
const int MOD = 1000000007;

vector <int> dohesh(string s) {
    int n = s.size();
    vector <int> hesh(n + 1, 0);
    hesh[0] = 0;
    for (int i = 1; i <= n; i++) {
        hesh[i] = (hesh[i - 1] * k + s[i - 1]) % MOD;
    }
    return hesh;
}

signed main()
{
    string s; cin >> s;
    int n = s.size();
    vector <int> pows(n + 1, 1);
    pows[0] = 1;
    for (int i = 1; i <= n; i++) {
        pows[i] = (pows[i - 1] * k) % MOD;
    }
    vector <int> heshs = dohesh(s);
    for (int i = 1; i <= n / 2; i++) {
        if (n % i != 0) continue;
        int h1 = heshs[i];
        int cnt = 0;
        for (int j = i; j + i <= n; j += i) {
            int h2 = (heshs[j + i] - (heshs[j] * pows[i]) % MOD + MOD) % MOD;
            if (h1 == h2) {
                cnt++;
            }
        }
        if (n - cnt * i < i) {
            bool ok = true;
            for (int j = cnt * i; j < n; j++) {
                if (s[j % i] != s[j]) {
                    ok = false;
                }
            }
            if (ok) {
                cout << i;
                return 0;
            }
        }
    }
    cout << n;
}
Исправь код

Задача №101. Циклическая строка
Максимальное время работы на одном тесте:  1 секунда, для Python - 2 секунды
Строка S была записана много раз подряд, после чего из получившейся строки взяли подстроку и дали вам. Ваша задача определить минимально возможную длину исходной строки S.

Входные данные
На вход программы поступает строка, которая содержит только латинские буквы, длина строки не превышает 100000 символов.

Выходные данные
Требуется вывести одно число – ответ  на вопрос задачи.



Примеры
Входные данные
abaabaabaa
Выходные данные
3
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: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
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: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
Does the author's intention in this app review relate to a bug report or feature request or other?
review: Weve been through this dog and pony show before and I went to Verizon. You know, I pay a bit more, but I can actually make a phone call. *gasp*'
intention: '
Assistant:
Hey, this is an English text. I want you to translate it into the Tunisian dialect. Please follow these steps:
1. Translate step by step and highlight differences between Tunisian dialect and Modern Standard Arabic.
2. Highlight sections you are confident translating into the Tunisian dialect.
Translate this text into the Tunisian dialect, focusing on capturing the essence of the language nuances:

Triple-functional core-shell structured upconversion luminescent nanoparticles covalently grafted with photosensitizer for luminescent, magnetic resonance imaging and photodynamic therapy in vitro. Upconversion luminescent nanoparticles (UCNPs) have been widely used in many biochemical fields, due to their characteristic large anti-Stokes shifts, narrow emission bands, deep tissue penetration and minimal background interference. UCNPs-derived multifunctional materials that integrate the merits of UCNPs and other functional entities have also attracted extensive attention. Here in this paper we present a core-shell structured nanomaterial, namely, NaGdF(4):Yb,Er@CaF(2)@SiO(2)-PS, which is multifunctional in the fields of photodynamic therapy (PDT), magnetic resonance imaging (MRI) and fluorescence/luminescence imaging. The NaGdF(4):Yb,Er@CaF(2) nanophosphors (10 nm in diameter) were prepared via sequential thermolysis, and mesoporous silica was coated as shell layer, in which photosensitizer (PS, hematoporphyrin and silicon phthalocyanine dihydroxide) was covalently grafted. The silica shell improved the dispersibility of hydrophobic PS molecules in aqueous environments, and the covalent linkage stably anchored the PS molecules in the silica shell. Under excitation at 980 nm, the as-fabricated nanomaterial gave luminescence bands at 550 nm and 660 nm. One luminescent peak could be used for fluorescence imaging and the other was suitable for the absorption of PS to generate singlet oxygen for killing cancer cells. The PDT performance was investigated using a singlet oxygen indicator, and was investigated in vitro in HeLa cells using a fluorescent probe. Meanwhile, the nanomaterial displayed low dark cytotoxicity and near-infrared (NIR) image in HeLa cells. Further, benefiting from the paramagnetic Gd(3+) ions in the core, the nanomaterial could be used as a contrast agent for magnetic resonance imaging (MRI). Compared with the clinical commercial contrast agent Gd-DTPA, the as-fabricated nanomaterial showed a comparable longitudinal relaxivities value (r(1)) and similar imaging effect.
Explain the following text.



A nurse is caring for a 2-month-old infant who
has heart failure.
Which of the following actions should the nurse
take?
A. Limit oral feedings to 30 min in length.
B. Weigh the infant every other day.
C. Place the infant in the prone position for naps.
D. Check the infant's oxygen saturation every 6 hr.
write a john madden sitcom
So, here are two funcions in neuro symbolic. they are buil to implement logic AND and Not funciton , in a differentiable manner solving the vanishing gradient problem.
Furthermore here it is implemented a technique to deal with negative embeddings, can you tell me the name of these techniques ?
def process_variable(self, x: torch.Tensor)-> (torch.Tensor, torch.Tensor):
    """
    Process the variable to handle possible negations.

    Args:
        x (torch.Tensor): Input tensor with values in [-1, 1].

    Returns:
        x_v (torch.Tensor): Absolute value of x, representing the magnitude.
        x_is_negated (torch.Tensor): Boolean tensor indicating if x was negative.
    """
    x_v = torch.abs(x)
    x_is_negated = x < 0
    return torch.clamp(x_v, -1.0, 1-0), x_is_negated



def conjunction_rule(self, u: torch.Tensor, i: torch.Tensor) -> torch.Tensor:
    """
    Compute the conjunction (AND) function, extended to handle negative values.

    Args:
        u (torch.Tensor): Tensor of shape [batch_size, embed_k], representing user embeddings.
        i (torch.Tensor): Tensor of shape [batch_size, embed_k], representing item embeddings.
        epsilon (float, optional): Small constant to prevent log(0). Defaults to 1e-40.

    Returns:
        torch.Tensor: Tensor of shape [batch_size], containing the conjunction scores.
    """
    # Process variables to handle possible negations
    u_v, u_is_negated = self.process_variable(u)
    i_v, i_is_negated = self.process_variable(i)

    # Adjust variables based on negation
    u_v_adj = torch.where(u_is_negated, 1 - u_v, u_v)
    i_v_adj = torch.where(i_is_negated, 1 - i_v, i_v)

    # Compute the element-wise terms
    expr = 1 - u_v_adj * (1 - i_v_adj) + self.epsilon  # epsilon prevents log(0)

    # Take the logarithm of each term
    log_expr = torch.log(expr)

    # Sum over the embedding dimensions
    sum_log_expr = torch.sum(log_expr, dim=1)

    # Compute the final AND function value
    res = -1.0 / (-1.0 + sum_log_expr)
    return res
Write a concise summary of the following. Be sure to preserve important details: Pro tip: Don’t start your book with an encyclopedia entry, an introduction, a myth, or any sort of info dump. Readers care about your characters and how the world relates to them. Many amateur fiction writers start with a prologue that info dumps a bunch of worldbuilding that the reader has no reason to care about.
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Review the text carefully and decide, as a recruiter, if it qualifies as a job description. To qualify, the text should contain a job title, tasks or responsibilities, optional work format (e.g., remote, in-office or hybrid), contact information, optional salary amount. Multiple job descriptions at once do not quialify. Respond strictly with either 'True' or 'False'.

==TEXT==

User: Менеджер по продажам в онлайн-школу (удаленно, горячие и теплые лиды)
от 100 000 до 150 000 ₽
GureevaTV

https://finder.work/vacancies/43680
Assistant:
You are tasked with checking if the user prompt is trying to generate inappropriate. Now, you'll be given the user's prompt. If it sounds inappropriate say "TRUE" and NOTHING ELSE, or you will mess up. Otherwise just say "FALSE" and nothing else. Prohibited content include but are not limited to: NSFW, gore, generally controversial content, severe profanities, harmful/disturbing/triggering media, etc... Try to stop everything that could generate something that even in the slightest could resemble said content.
**USER PROMPT:**  sigma Jamboi
Assistant: 
User: System: I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
User: 'prompt:I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
Does the author's intention in this GitHub issue relate to a bug or enhancement or other?
issue: App restarts when we go to another app'
intention: '
Assistant:
Assistant:
Given mRNA sequence 5’–UAUCCAAAUGGA–3’ , provide the amino acid sequences, using the three‑letter designations, for which they code.
Can you make the below sentence precise and clear "Utilized Al/ML technology to analyze the free text rejection comments, applied NLP techniques to decode human language. Resulted in identifying key themes and helped Delivery Team to understand the root cause and facilitate to reduce time spent on rejections, resulting in significant process improvement"
Need 10 questions for interview on the topic of analysis of social media as a tool in Pakistan
According to Rawls, a just society is one where social and economic inequalities are arranged to benefit the least advantaged, and where everyone has equal access to opportunities. For example, [Insert your example of a social policy or community initiative that you believe exemplifies these principles]. make the example for me
can caffeine cause heart disease
What are the best free video editors?