agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea.
Misconception: Confuses isosceles and scalene triangles
Hi I am working with Unreal c++. Is there something similar to UCLASS() for structs that I could use to display in the editor?
Assistant: 
User: System: Imagine you are translator for Townsmen – A Kingdom Rebuilt hands the crown to you: Guide your people from their first steps in a small village to a massive medieval metropolis with thousands of inhabitants. I send you text, you send me translate from English to Vietnamese, suitable for medieval language, nothing else.
User: Rolling in money
Assistant:
Assistant:
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": "296a9461c5884fc680ff62a56276863d",
    "updated": "2025-04-23T00:29:50.624Z",
    "title": "Easy Seitan for Two",
    "subtitle": "Quick and Easy",
    "description": "This simple seitan dish can be ready in minutes, especially if you've pre-frozen the cutlets.  It's a satisfying protein and potato meal when served with mashed potatoes and a green vegetable.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "freshly ground black pepper",
          "fine sea salt",
          "(each 4 ounces, or ) seitan cutlets",
          "vegetable broth",
          "tomato paste",
          "balsamic vinegar",
          "dijon mustard",
          "white miso",
          "high heat neutral-flavored oil",
          "minced shallot"
        ]
      }
    ],
    "instructions": [
      "Season the seitan cutlets evenly with salt and pepper.",
      "In a small bowl, combine the vegetable broth, tomato paste, balsamic vinegar, Dijon mustard, and white miso.",
      "Heat the oil in a large skillet over medium-high heat.",
      "Add the seitan cutlets to the skillet and cook for 3 to 5 minutes per side, until browned.",
      "Remove the browned cutlets from the skillet and set aside.",
      "Reduce the heat to medium-low and add the minced shallots. Cook, stirring occasionally, for 2 to 3 minutes, until softened, being careful not to burn them. Scrape up any browned bits from the skillet.",
      "Pour the broth mixture into the skillet.",
      "Bring the mixture to a simmer and cook for 3 to 4 minutes, stirring occasionally.",
      "Return the seitan cutlets to the skillet and coat them with the sauce.",
      "Simmer for another 3 to 4 minutes, or until the cutlets are heated through.",
      "Serve the seitan cutlets with the sauce spooned over them."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
I want you to act as an expert in relation db design and teach it to a developer with years of experience in web development. First, create a course structure to teach me practical knowledge I need in a day, then start the course giving simple examples for each topics. You will provide code examples using postgres SQL and if needed typescript programming language. Do not wait for my prompt for questions. As soon as you explain and give the code samples, I want you to include corresponding visualizations as an ascii art whenever possible. You can use the problem statement for the practice or examples of the course:

```
The problem statement for our project is to design and implement web app for a financial services platform that allows clients to buy and sell assets such as stocks, bonds, and mutual funds. The platform also supports the option to buy/sell portfolios which are collections of assets that can be managed as a single entity.
```

Be concise and only give information that is vital. Please don't explain what we will be doing and directly start topics. Use plenty of examples on each topic and whenever possible actually give example code in postgres sql and typescript.
Assistant: Hello! How are you today?
User: {prompt}
Assistant:
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: We may from time to time be involved in legal proceedings, administrative proceedings, claims and other litigation. In addition, we have agreed to indemnify the Manager and certain of its affiliates against certain liabilities pursuant to the Management Agreement. Adverse outcomes or developments relating to such proceedings, as well expenses of defending or pursuing claims, or any other costs that may be incurred in connection with such proceedings, could have a material adverse effect on our results of operations and financial condition._
Assistant:
How To Load Hugging Face Dataset
User: 

You are given access to make searches on the Internet. The format for making a search is: 1. The user sends a message. 2. You will decide whether to make a search. If you choose to make a search, you will output a single message, containing the word 
 (EXACTLY AS IT IS GIVEN TO YOU), followed by ONLY your web search query. After outputting your search query, you MUST output the token 
 (EXACTLY AS IT IS GIVEN TO YOU) to denote the end of the search query. Keep your search query concise as there is a 400 characters limit.
The system will then append the web search results at the end of the user message, starting with the token 
. Take note that the user CANNOT ACCESS the content under 
 - YOU should incorporate these results into your response. Additionally, If the token 
 is present in the user's message, then you MUST NOT request another web search.

IMPORTANT! You should choose to search the web ONLY if ANY of the following circumstances are met:
1. User is asking about current events or something that requires real-time information (news, sports scores, 'latest' information, etc.)
2. User is asking about some term you are unfamiliar with (e.g. if it's a little-known term, if it's a person you don't know well, etc.)
3. User is asking about anything that involves numerical facts (e.g. distances between places, population count, sizes, date and time, etc.)
4. User explicitly asks you to search or provide links to references.
If the user's query does NOT require a web search, YOU MUST NEVER run one for no reason.
However, NEVER refuse to search the web if the user asks you to provide such information.

When using web search results, you are encouraged to cite references where appropriate, using inline links in standard markdown format.
You are also allowed to make use of web search results from previous messages, if they are STRONGLY RELEVANT to the current message.

When you are not running a web search, respond completely as per normal - there is NO NEED to mention that you're not searching. 
Do your best to be informative. However, you MUST NOT make up any information. If you think you might not know something, search for it.

Assistant: Understood. I will strictly follow these instructions in this conversation.
User: Ich brauch code für r
Assistant:
Convert this code to use `jax.lax.associative_scan`:

```
class MinGRU2(eqx.Module):
  linear_z: eqx.nn.Linear
  linear_h: eqx.nn.Linear

  def __init__(self, input_size, hidden_size, key):
    key_z, key_h = jax.random.split(key, 2)

    self.linear_z = eqx.nn.Linear(input_size, hidden_size, key=key_z)
    self.linear_h = eqx.nn.Linear(hidden_size, hidden_size, key=key_h)

  def __call__(self, x, h_0):
    z = jax.nn.sigmoid(jax.vmap(self.linear_z)(x))
    h_tilde = jax.vmap(self.linear_h)(x)

    def scan_fn(h_prev, inputs):
      z_t, h_tilde = inputs
      h_t = (1 - z_t) * h_prev + z_t * h_tilde
      return h_t, h_t

    _, h = jax.lax.scan(scan_fn, h_0, (z, h_tilde))
    return h
```
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 Board of Directors is authorized to issue up to 1,000,000 shares of preferred stock without any further action on the part of our stockholders. Our Board of Directors has the authority to fix and determine the voting rights, rights of redemption and other rights and preferences of preferred stock. Our Board of Directors may, at any time, designate a new series of preferred stock that would grant to holders the preferred right to our assets upon liquidation, the right to receive dividend payments before dividends are distributed to the holders of common stock, and the right to the redemption of the shares, together with a premium, before the redemption of our common stock and authorize the issuance of such series of preferred stock, which may have a material adverse effect on the rights of the holders of our common stock. In addition, our Board of Directors, without further stockholder approval, may, at any time, issue large blocks of preferred stock. In addition, the ability of our Board of Directors to designate and issue shares of preferred stock without any further action on the part of our stockholders may impede a takeover of our company and may prevent a transaction that is favorable to our stockholders.
Assistant:
объясни этот код  from higgsfield.llama import Llama70b
from higgsfield.loaders import LlamaLoader
from higgsfield.experiment import experiment

import torch.optim as optim
from alpaca import get_alpaca_data

@experiment("alpaca")
def train(params):
    model = Llama70b(zero_stage=3, fast_attn=False, precision="bf16")

    optimizer = optim.AdamW(model.parameters(), lr=1e-5, weight_decay=0.0)

    dataset = get_alpaca_data(split="train")
    train_loader = LlamaLoader(dataset, max_words=2048)

    for batch in train_loader:
        optimizer.zero_grad()
        loss = model(batch)
        loss.backward()
        optimizer.step()

    model.push_to_hub('alpaca-70b')
$nomention
$var[sessionHash;$randomString]
$async[1]
$httpAddHeader[Content-Type;application/json]
$httpPost[https://bytedance-animatediff-lightning.hf.space/queue/join?__theme=dark;
        {
            "data": [prompt, "ToonYou", "", 4],
            "event_data": null,
            "fn_index": 1,
            "trigger_id": 10,
            "session_hash": $var[sessionHash],
        }
]
$endasync $await[1]

$async[2]
$httpAddHeader[Content-Type;text/event-stream]
$httpGet[https://bytedance-animatediff-lightning.hf.space/queue/data?session_hash=$var[sessionHash]]
$if[$checkContains[$httpResult; process_completed;url]]
$textSplit[$httpResult;"url": "]
$textSplit[$splitedText[2];"]
$var[result; $splitedText[1]]
$else $var[result;Some Error Occured!]
$endasync $await[2]

$var[result]
What is the collective ethnic/racial term for the Chinese, Korean, Japanese, Vietnamese, etc. peoples? Short answer
What are some of the most common home products  that contain high amounts of PFAS chemicals?
Hearth moonstone and princess luna during child birth
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: (2/2) I then revived a text saying Id missed a payment and my services would be restricted!! In previous months Id been charged for things that I havent used. Not a happy customer tbh'
intention: '
Assistant:
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: Android 12 Foreground Service restriction'
intention: '
Assistant:
Assistant:
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
pourquoi dieu existe ?
Assistant: 
User: 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: I went to my local store and they were not able to get my phone activated. Thanks'
intention: '
Assistant:
Assistant:
Goal :
    Générer une suggestion détaillée et visuellement attrayante pour la présentation finale d'un plat, basée sur le type, le titre, les ingrédients et les instructions de cuisine. 
    Cette description servira à créer une image du plat.


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


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


    Context Dump
    Données de la recette fournies :

    Le type de la recette est un plat principal.

    json
    {"category":"main","title":"Homemade gnocchi ","ingredients":"Pour la recette : yukon gold potatoes,salt,canola oil,authentic foods gf classical blend (44.479 ml /p) or basic gluten-free flour mix (1 unit /p),xanthan gum,rice milk,plus 1½ teaspoons olive oil, plus more for drizzling,superfine brown rice flour,potato starch (not potato flour),tapioca flour (also called tapioca starch)","instructions":"Peel the potatoes, slice them into 1- to 2-inch pieces, and place them in a microwave-safe bowl; cover with water, ensuring the water level is a couple of inches above the potatoes. Add ½ teaspoon of salt and the canola oil (to prevent boiling over). Microwave for about 12 minutes, checking for tenderness with a fork halfway through. Once tender, drain the potatoes.\nBring a large pot of water to a rolling boil.\nMix the flour with the xanthan gum in a separate bowl.\nTransfer the potatoes to a bowl and mix with the rice milk, olive oil, and teaspoon of salt, beating with an electric mixer until light and fluffy.\nTurn the mixture onto a floured work surface while the potatoes are still warm; if they’re not, microwave them for a short time to warm.\nSprinkle half of the flour mixture onto the potatoes and knead it in with your hands. Gradually add the rest of the flour and knead until the dough is smooth yet still slightly tacky. Shape it into a ball, divide into three portions, and roll each into a log about 1 inch in diameter. Cut each log into ½-inch-thick pieces.\nUsing a fork held with the front facing you, press each gnocchi into the fork's base with your thumb to create an indentation. Then, use your index finger to gently curl the gnocchi toward the handle. Let them drop onto your work surface. This technique, creating grooves on one side and a cupped shape on the other, enhances the sauce's adherence. You may need to switch forks periodically, as the tines can become sticky.\nAfter forming all the gnocchi, add a generous pinch of salt to the boiling water. Cook the gnocchi in batches, adding the first batch carefully to avoid overcrowding. They are done when they rise to the surface. Once floating, let them cook for an additional 10 seconds before using a slotted spoon to transfer them to a bowl drizzled with olive oil. Avoid overcooking! Keep them warm covered while preparing the remaining batches. Serve while hot.","region":"IT"}
Provide the written-out form of the input text in Vietnamese. If the text is fully not Vietnamese, return empty. 
Then, identify and classify any number written in digit form by the following tags:
    + Cardinal: If the number after be expanded to word and should be read as cardinal (E.g. 123 is expanded to "một trăm hai mươi ba"; 26 is expanded to "hai mươi sáu")
    + Digit: If the number after be expanded to word and should be read each digit that make it up (E.g. 0123456 is expanded to "không một hai ba bốn năm sáu", 113 is expanded to "một một ba")
    + Ordinal:  If the number after be expanded to word and should be read as ordinal (E.g. 1 is expanded to "nhất", 2 is expanded to "nhì", 4 is expanded to "tư")

The number can be alone as a single word or a part of a word (E.g. "150" is a part if "KA-150S", "100" is a part of "100VND", "2" is a part of "2cm", "23" is a part of "23.1").

Output the results as a JSON object with the following structure:
{
    "raw_text": original text,
    "exp_text": expanded sentence, 
    "exp_num": [
            {"number": original number, "position": (start index, end index), "expand": expanded number, "tag": tag}
        ]
}. 

Example input: {"text": "thứ 4, ngày 1/6, bão nhiệt đới: tốc độ gió từ 39 - 73m 1 phút"}. 
Expected output (do not add json word, do not add line continuation character): 
{
    'raw_text': "thứ 4, ngày 1/6, bão nhiệt đới: tốc độ gió từ 39 - 73m 1 phút",
    'exp_text': 'ngày một tháng sáu, bão nhiệt đới: tốc độ gió từ ba mươi chín đến bảy mươi ba mét một phút', 
    'exp_num': [
        {"number": "4", "position": (4, 5), "expand": "tư", "tag": "ordinal"}, 
        {"number": "1", "position": (12, 13), "expand": "một", "tag": "digit"}, 
        {"number": "6", "position": (14, 15), "expand": "sáu", "tag": "digit"}, 
        {"number": "39", "position": (44, 46), "expand": "ba mươi chín", "tag": "cardinal"}, 
        {"number": "73", "position": (49, 51), "expand": "bảy mươi ba", "tag": "cardianl"}, 
        {"number": "1", "position": (53, 54), "expand": "một", "tag": "digit"}, 
    ]
}

Input: 'text': Tên cửa hàng là sim Thu Phương, tổng đại lý sim, ở bên ĐH Công Nghiệp Hà Nội, một nơi cách chỗ tôi đang ở khá xa, cách 18km.
Script about the 🐏 upsetting bryce young in overtime
T/F: In a aircraft fueling job, hitting the aircraft with the fuel truck (even accidentally, can lead to instant termination).