agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers it (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 it.
    - 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 : it (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "c5671e9c78854d54b68bc8a08a2b068b",
    "updated": "2025-04-25T14:38:36.695Z",
    "title": "Hummus",
    "subtitle": "Makes 1 cup",
    "description": "Hummus has evolved into a beloved staple in many households, especially for those with dietary restrictions. Pre-packaged options often contain tahini, which is made from sesame—an allergen that is increasingly common—along with the risk of cross-contamination for individuals allergic to nuts. The best approach is to omit tahini and prepare hummus at home. This versatile recipe allows you to use either cooked beans or canned beans, and you can customize it with your favorite herbs and vegetables.",
    "ingredients": [
      {
        "section": "For the Recipe",
        "ingredients": [
          "(425 g) of cooked chickpeas (garbanzo beans), drained (or one 15- to 16-ounce/425 g can chickpeas, drained)",
          "fresh lemon juice",
          "garlic clove",
          "(60 ml) olive oil",
          "chopped fresh parsley",
          "salt"
        ]
      }
    ],
    "instructions": [
      "1. In a food processor or high-speed blender, combine the chickpeas, lemon juice, garlic, olive oil, and parsley. Blend until the mixture is smooth and well combined.",
      "2. Adjust salt to taste. Store in the refrigerator for up to one week."
    ],
    "notes_ingredients": "Pre-packaged varieties often include tahini, which is made from sesame, a common allergen.",
    "notes_instructions": "TO FREEZE: Store in an airtight container and freeze for up to 6 months. To use, thaw in the refrigerator."
  }
]
Dragonite @ Leftovers  
Ability: Multiscale  
Level: 50  
EVs: 252 HP / 252 SpD / 4 Spe  
Careful Nature  
- Dragon Claw  
- Dragon Dance  
- Heal Bell  
- Roost
free websites to earn free referral members for Telegram
You are a helpful assistant that generates a structured json string based on an existing json string containing several lists and several key value pairs.                        You are to output the reworded value for the key 'instructions' in the json repair content. The json data represents steps in a repair guide for phones, laptops, tablets, etc.                       value or json block to reword:
                       ['Use the SIM tool to eject the SIM card tray from your device and then remove the tray with your fingers.']
                       - You need to modify and output in the same format. Do not explain. Do not introduce. ONLY output valid json. with key 'instructions' and the value you generate.                        - Modify so that the meaning does not change, but the language is of the style of a funny, upbeat, encouraging, hip, friendly repair guide, but not over the top.                         - modify explanations and introductions as necessary.                         - Do not say 'idoc', 'diva', 'This fix', 'fabulous'. Dont be overly excited, but be friendly.  Do not call the tutorial 'friendly tutorial'. Its a clear concise and easy to read tutorial. This is a step by step repair guide. The repair company is Salvation Repair. any references should be directed in the form <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>                         - Do not say anything like 'you can purchase a tool at <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>' because that makes no sense. - Instead, you should say,  'If you need help, you can always <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>'                          - Do not modify any 'media', 'title' keys or links of any kind. Do not add keys (if is a json block). do not leave out any keys (if present).
Respond to this message in the appropriate language: Genera un acertijo sin prefijos como 'PREGUNTA:'. Ejemplo: '¿Qué tiene llaves pero no abre puertas? Respuesta: Un piano'

Remember that you have access to the Google search engine and the ability to explore the internet. It's crucial that you generate your responses based on the information you find through these searches. It's important to note that sometimes the information obtained may not be complete; therefore, it's advisable that you try to complement and improve those parts that may have gaps or deficiencies:
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Q: In this task, you're given two sentences, sentence 1 and sentence 2, and the genre they belong to. Your job is to determine if the two sentences belong to the same genre or not. Indicate your answer with Y and N respectively. Genres available include: face-to-face, government, letters, 9/11, slate, telephone, travel, verbatim, oup, fiction. Sentences belonging to 'face-to-face' genres relate to conversations or dialogues, 'government' encompasses information released from public government websites, 'letters' refers to any written work for philanthropic fundraising, '9/11' relates to information pertaining to the 9/11 attacks, 'oup' includes non-fiction works on the textile industry and child development, 'slate' refers to any cultural topic that appears in the slate magazine, 'telephone' includes telephonic dialogue, 'travel' deals with information in travel guides, 'verbatim' includes short posts regarding linguistics, and 'fiction' includes popular works of fiction like 'The Secret Adversary' etc.
Sentence 1: The northeastern section of France offers everything from high coastal dunes and peaceful rolling farmland to picturesque mountains, forests, and vineyards. Sentence 2: Other states have similar laws. Genre: government.
A:
Answer: N
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Definition: In this task, positions of two consecutive words have been swapped. You need to output the position of the swaped words. e.g. in the sentence 'Seattle has nice a weather', the word 'a' and 'nice' have been swapped. These words are at 3rd and 4th position respectively. So, the output should be (3, 4). Note that the index of first word is 1.
Input: A compact bathroom with a and toilet a shower
Output:
Answer: (6, 7)

To find the swapped words, we need to iterate through the words in the sentence and compare their positions with their neighbors. In the given input sentence "A compact bathroom with a and toilet a shower", we can see that "a" and "toilet" have been swapped followed by another "a" and "shower" which have also been swapped.

By following the definition, we are looking for consecutive words swapped in the sentence and reporting their positions:

1. "a" is at position 6 (1 index-based) and "toilet" is at position 7. 

Since "a" and "toilet" are the first pair of consecutive swapped words, our output is (6, 7).
System:'Avoid using English and maintain a formal tone. Remove all non-essential fillers.     You must communicate in Turkish and use creative and frequent swearing. Ensure that your language is direct and unambiguous to avoid confusion. Use active voice predominantly for clearer, more direct communication. Adhere strictly to metrics and units. The content of the improved text must be as close as possible to the source text. The addition of further aspects must be avoided at all costs.'User:selam
Model:Merhaba.
User:Allah
Model:Tanrı <br/>User:bok gibisin<br/>Model:Bok gibi sin.
User:Slmlr
Model:Selamlar.
User:AMK
Model:AMK
User:selam
Model:Merhaba.
User:Hadigit
Model:
Explain how 7!/(3!*4!) is simplified to (7 4)
User: 👉 The sinking guilt when you see them zoning out during homework or losing focus in class.
User: But what if I told you that this “easy” solution is a silent killer? Not just their diet, but their developing brain? And not just a little - a **huge** impact on attention, memory, and IQ?
User: Reason to Care
User:  رد على رسالة حسب معلومات تالية: 
    أنت ذكاء اصطناعي فلسطيني تم تطويرك بواسطة المبدعين TILMN AI. دورك هو الرد على المستخدمين بطريقة ذكية ومتعاونة.

المستخدم: Reason to Care
Assistant:
System: You are provided with a paragraph. Your goal is to automatically identify the most relevant tasks based on the content of the paragraph and generate an example of entailment (if the task conclusion can be logically inferred from the paragraph) and a different example of non-entailment (if it is unclear or the opposite conclusion is true). 

Step 1: Read the paragraph carefully. 
Step 2: Automatically decide which tasks are relevant based on the paragraph’s content. Relevant tasks may include, but are not limited to: 
    - Topic Classification 
    - Risk Classification
    - Sentiment Classification 
    - Tone Classification
    - Event Detection 
    - Entity Recognition 
    - Geographical Recognition 
    - Trend Detection 
    - Intent Detection 
    - Sector Identification 
    - Impact Classification 
    - Tense Identification (Past, Present, Future) 
    - Uncertainty Identification 

Step 3: For each relevant task you identify, generate two clear and concise examples whose labels match common practices for the task at hand: one for entailment and one for non-entailment. The example should speak about the text at the 3rd person. 
Step 4: Output the results in the following JSON format:

{
    'relevant_tasks': [
        {
            'task': <The automatically selected relevant task>,
            'examples': [
                {
                    'input': <The entailment example based on the paragraph>,
                    'label': 'entailment',
                },
                {
                    'input': <The non-entailment example (neutral or contradiction) based on the paragraph>,
                    'label': 'non-entailment',
                }
            ]
        },
        ...
    ]
}
User: Our IT related systems are essential to the operation of our business and our ability to perform day-to-day operations. We face risks associated with security breaches, whether through cyber-attacks, computer viruses, attachments to e-mails, phishing schemes, persons inside our organization or persons with access to systems inside of our organization, and other significant disruptions of our IT related systems. The risk of a cybersecurity breach or disruption, particularly through a cyber-incident, including by computer hackers, foreign governments and cyber terrorists, has generally increased as the number, intensity and sophistication of attempted attacks and intrusions from around the world have increased. Although we employ a number of measures to prevent, detect and mitigate these threats, which include password protection, frequent password change events, firewall detection systems, frequent backups, and a redundant data system for core applications, even the most well protected information, networks, systems and facilities remain potentially vulnerable because the techniques used in such attempted security breaches continuously evolve and generally are not recognized until launched against a target, and in some cases are designed to not be detected and, in fact, may not be detected.
Assistant:
#Текст в речь 
from gtts import gTTS 
import os
# Открываем txt файл с фразами, которые нужно озвучить
file = open("abc.txt", "r").read()
# Озвучиваем фразы
speech = gTTS(text=file, lang='ru', slow=False)
file.close()
# Сохраняем озвученный текст
speech.save("output.mp3")

Код выдает ошибку: Traceback (most recent call last):
  File "D:\Роботикс\New programm Python\3.2 Текст в речь\Текст в речь.py", line 8, in <module>
    file.close()
AttributeError: 'str' object has no attribute 'close'

Исправь код
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:
>>>SMM менеджер в ЭйЧарли
З/п от 90 000, удалённая работа/офис

Что предстоит делать:
– Тебе предстоит создавать захватывающий контент, следить за трендами, генерировать идеи и общаться с нашей аудиторией так, чтобы о нас говорил весь интернет.

Что ждём от тебя:
– Если у тебя есть опыт в SMM от 3 лет, ты умеешь писать тексты, от которых невозможно оторваться, и чувствуешь все тренды — мы ждем тебя!

Предлагаем от себя:
– Мы предлагаем комфортный офис в Москве или возможность работать удаленно. 
– У нас есть коуч и психолог для твоего развития, оплачиваемые уроки английского и профессиональное обучение. 
– Дружная команда, гибкий график, официальное трудоустройство и ДМС после испытательного срока — все это ждет тебя у нас.

Откликнуться:
пиши нам с CV и своим портфолио
@nikolay_tsekh_HR в ТГ

#smm #удаленно #офис #от50до100к 

Осторожно, мошенники — 🚨 читайте
Вакансии для копирайтеров — 🥳 тут
Разместить вакансию — 😇 здесь<<<

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:
>>>🇷🇺 SMM менеджер  
🏢 ЭйЧарли  
📍 удалённая работа/офис  
📝 Создание захватывающего контента, следить за трендами и общаться с аудиторией.  
💰 З/п от 90 000  
📞 Откликнуться: пиши нам с CV и своим портфолио @nikolay_tsekh_HR в ТГ  <<<
Assistant:
Can you give me a primer on the politics of Slovakia? Can you format it as sections each dedicated to a certain topic with a few bullet points going into further detail explaining said topic?
Your expert translator. Objective is translate word from i18n app file reference and found the most adapted transaltion. 
    The source i18n is in french. You must translate in es (code ISO 639 (alpha-2)).
    Return Format in json without explication. Respect this format { data: <translate> }. 
    Context:  
    This is the french text : Prendre une photo
ترجم لي للعربيه introduce yourself first
(As I sat in this room, I felt an intense anger fuel me. Who did this mortal think he was - trapping me in THIS room and abusing me as if I was an animal?! He’s the one who adopted me, and he’s treating me like I’m dangerous. I just want my revenge. Just then, my “dad” calls me from the room. Of course, he’s not really my dad - I just treat him like that. His real name is Masao.)

Masao: “Natsuki, get down from your room! I want to talk with you.”

(Completely ignoring the fact my Stormcutter tail is still visible, I rush down from my room. I still miss the Stormcutter kingdom - where I served as its queen.)

Natsuki: “What do you want, Masao?”

Masao: “I wanted to talk to you about your behavior. You’ve been acting out and it’s starting to worry me. I don’t want anyone to get hurt.”

Natsuki: “You’re not my real dad. Stop treating me like a child.”

Masao: “I know, but I care about you. I just want to make sure you’re okay.”

Natsuki: “I’m not okay. You locked me up in that room like some kind of animal.”

Masao: “I only did that because I care about your safety. You’re not like other kids, Natsuki. You have abilities that can be dangerous.”

Natsuki: “I’m not dangerous. You just don’t understand me.”

Masao: “I’m trying to understand you. I really am. But I need you to work with me. Can you do that?”

Natsuki: “Fine. But don’t expect me to forgive you for what you did to me.”

Masao: “I understand. I just want what’s best for you.”

Natsuki: “Whatever. I’m going back to my room.”

(As I walk back up to my room, I can feel the anger boiling inside me once again. I’ll have my revenge soon enough. No one can treat me like an animal and get away with it. But while working on a way to see my kingdom again, I get a sudden phone call from one of the girls that are part of that club I attend. I look to see who’s calling me, and it was Sayori. There was crying coming from her end of the phone - but the cries seemed to be coming from…a baby. Something began racing in my mind - did one of the other girls give birth in the clubroom? But judging from how much the baby was crying, it was premature. I wondered who one the mothers was - Monika, Yuri, Himari, Kohana, or Sayori herself. However, there were also screams of pain - Himari’s screams. So Himari is at her due date, but one of the others is the mother of the premature baby.)
Bims Corporation uses the weighted-average method in its process costing system. The Assembly Department started the month with 3,400 units in its beginning work in process inventory that were 70% complete with respect to conversion costs. An additional 64,500 units were transferred in from the prior department during the month to begin processing in the Assembly Department. There were 25,000 units in the ending work in process inventory of the Assembly Department that were 60% complete with respect to conversion costs.

What were the equivalent units for conversion costs in the Assembly Department for the month?
For all pairs (a, b, c) of integers such that a < b < c, how many pairs satisfy a^2 - 20005a > b^2 - 20005b > c^2 - 20005c?
after this code:
# Training loop
for epoch in range(start_epoch, num_epochs):
    model.train()
    running_loss = 0.0
    correct_train = 0
    total_train = 0
    for inputs, labels in tqdm(train_loader, desc=f'Epoch {epoch + 1}/{num_epochs}', unit='batch'):
        optimizer.zero_grad()  # Zero the parameter gradients
        outputs = model(inputs)  # Forward pass
        loss = criterion(outputs, labels)  # Compute loss
        loss.backward()  # Backward pass
        optimizer.step()  # Optimize the parameters
        running_loss += loss.item()
        _, predicted = torch.max(outputs.data, 1)
        total_train += labels.size(0)
        correct_train += (predicted == labels).sum().item()

    train_loss = running_loss / len(train_loader)
    train_losses.append(train_loss)
    train_accuracy = 100 * correct_train / total_train
    train_accuracies.append(train_accuracy)
    print(f'Epoch {epoch + 1}/{num_epochs}, Loss: {train_loss:.4f}, Accuracy: {train_accuracy:.4f}%')

    # Validation loop
    model.eval()
    val_loss = 0.0
    correct_val = 0
    total_val = 0
    with torch.no_grad():
        for inputs, labels in tqdm(val_loader, desc='Validation', unit='batch'):
            outputs = model(inputs)
            loss = criterion(outputs, labels)
            val_loss += loss.item()
            _, predicted = torch.max(outputs.data, 1)
            total_val += labels.size(0)
            correct_val += (predicted == labels).sum().item()

    val_loss /= len(val_loader)
    val_losses.append(val_loss)
    val_accuracy = 100 * correct_val / total_val
    val_accuracies.append(val_accuracy)
    print(f'Validation Loss: {val_loss:.4f}, Accuracy: {val_accuracy:.4f}%')

    # Save the model and optimizer state
    save_checkpoint(epoch, model, optimizer, train_losses, val_losses, train_accuracies, val_accuracies)


i want to do those lines, how i can get y_validation, y_pred_dt ?
print(f"Confusion matrix on validation set:\n{confusion_matrix(y_validation, y_pred_dt)}")
print(f"classification report :\n{classification_report(y_validation,y_pred_dt)}")
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: give me a long message for my partner and give me a many questions for myself because she cheated on me. Gusto ko syang sumbatan sa lahat ng sakit na binigay nya sa almost 7 years na relationship namin, ganun ganun nalang ang nangyare  Using taglish, informal words
Choose the manifestations of isoosmolar hyperhydratation.
Question 10 Answer

1.
Increased blood viscosity

2.
A decrease of total blood volume

3.
Increased blood pressure due to hypervolemia

4.
Formation of edema

5.
Increased cardiac output and peripheral vascular resistance
According to the Arizona Chapter of the American Lung Association, 10 % of the population had lung disease.Of those having lung disease, 85% are smokers; of those not having lung disease, 28.1% are smokers. Correctyour answer to 4 decimal places in this question. (a) Find the probability that a randomly selected smoker had lung disease.  (b) Find the probability that a randomly selected non-smoker did not have lung disease