agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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 clients sometimes invest in companies with weak financial conditions, poor operating results, substantial financial needs, negative net worth and/or special competitive or regulatory problems. These clients also invest in companies that are or are anticipated to be involved in bankruptcy or reorganization proceedings. In such situations, it may be difficult to obtain full information as to the exact financial and operating conditions of these companies. Additionally, the fair values of such investments are subject to abrupt and erratic market movements and significant price volatility if they are publicly traded securities, and are subject to significant uncertainty in general if they are not publicly traded securities. Furthermore, some of our clients’ distressed investments may not be widely traded or may have no recognized market. A client’s exposure to such investments may be substantial in relation to the market for those investments, and the assets are likely to be illiquid and difficult to sell or transfer. As a result, it may take a number of years for the market value of such investments to ultimately reflect their intrinsic value as perceived by us, if at all.
Assistant:
i have a lot of fat in my chest and not enough muscle So my chest is kinda fluffy So i need a workout program that contains 4 days Chest to get my chest looks cooler and better than it is and the equipments is (Pull up bar- BodyWeight , Dumbbell (5-10 Kgs), gymnastic rings  )
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] The Angel Next Door Spoils Me Rotten S01E11 [BDRip 720p x265 10bit] [Dual Audio] ESub.mkv
Create 3 LinkedIn posts about the value of traveling full time that mention Heather Markel's full-time travel services and mention her website https://heatherbegins.com
I have a list of ingredients that I would like to format in a simple and consistent way, following this structure:

"Quantity Unit Description."

Formatting Rules:

Quantity must be a number (e.g., "200" instead of "two hundred").

Unit must use the metric system and the corresponding abbreviated form (e.g., grams → g, liters → l, milliliters → ml, etc.).

Description should be the ingredient, including any specific details if mentioned (e.g., "brown sugar", "melted unsalted butter").

If an ingredient is already formatted correctly, do not change it.

Do not invent a quantity or unit if none is provided — leave it as is and just include the description.

If a line includes alternatives or multiple options (e.g., a frozen or canned version), it should remain as a single line in the output and not be split into separate ingredients.

Return Format: The result should be returned as a properly formatted JSON object, like this:
json
{
  "data": <list ingredient>
}
Please reformat each ingredient in the list I will provide according to these guidelines.

Context Dump
Ingredients source provided:
1¾ cup plus 1½ tablespoons (10 ounces) bread flour, plus more for rolling,1 teaspoon fine sea salt,3/4 cup room-temperature water
explain me about stp
Below is a paragraph from an academic paper. Polish the writing to meet the academic style, improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. Furthermore, list all modification and explain the reasons to do so in markdown table. Paragraph: With the worsening of energy crisis and environmental problems, it is urgent to reduce the use of fossil fuels and develop renewable energy and clean energy. The disadvantages of renewable energy such as photovoltaic and wind power are not easy to store and low efficiency. If the unstable photoelectric wind power is used to electrolyze water to produce hydrogen, both the electric energy is fully utilized and the hydrogen is obtained. Hydrogen has high calorific value and fast burning rate, but the production price is high, and the storage and transportation cost is high. So people are turning to ammonia fuel as an alternative, which has a relatively high hydrogen content.  Ammonia is an ideal renewable carbon-free fuel and hydrogen storage carrier, resulting in nitrogen and water completely burned in oxygen. However, ammonia is difficult to burn off, the combustion efficiency is very low, and the nitrogen oxide emission is high.  In order to improve the combustion rate and performance of ammonia, combustible gases such as CH4 and CO can be mixed with ammonia.  At present, the study on the effect of mixed gas on the production of NO in NH3 combustion is not perfect . In this paper, the NO formation behaviors during the combustion of NH3/CH4 and NH3/CO mixtures were investigated by using a the high-temperature furnace reaction system was used to design combustion experiments on NH3/CH4/Ar and NH3/CO/Ar blends under different conditions, . The influences from co-firing CH4 and CO on the NO generation of NH3 combustion was further analyzed via adopting experimentsand the generation of NO from the combustion of mixed fuel gases under different mixing blending ratios, excess air coefficient, temperature, residence time and fuel concentration was investigated.
-- Initial table
local table = {
   [1] = {['item1'] = 1, ['item2'] = 2, ['item3'] = 3, ['item4'] = 4},
   [2] = {['item1'] = 1, ['item2'] = 2, ['item3'] = 3, ['item4'] = 4}
}

Lua 
how can I get the sum of all the values in the sub table of [1]
Discuss the importance of early recognition and prompt medical intervention IN HEART FAILURE.
I am using Behringer X32 to conduct live sound. However, I am also routing a signal into Logic Pro X for separate mix for our live stream. The playback from the computer has a substantial reverb effect that does not come from my computer or Logic Pro X mix. Can you assist with this routing? Thanks!
Decimal place value with regrouping
Google Classroom

Microsoft Teams
Problem
\[2.10\] is equivalent to how many tenths?
\[2.10 = \] 
 tenths
Related content
Report a problem


Do 7 problems
Give me for 20 quotes in alice in wonderland about dreams and analyzing dreams?
Write an extremely long story set in the backrooms about a man named Steven. Have everyone exclusively call the backrooms "The Halls". The safe zone is inhabited by a group if 20 other survivors in a section of the halls called "The Safe Zone" which looks like a normal town and is entirely safe since entities cannot enter the town. Steven somehow got turned into a busty female anthropomorphic lizard. Steven doesnt know he was turned into a woman yet. Have the story start with Steven waking up in the safe zone, he has no idea how he got there and is confused why he cant remember anything about his life, he then realizes hes a girl and freaks out. A nerdy man named Lost calms Steven down. Steven explains he was a guy and frantically asks why he has huge tits and why he cant remember anything. Steven eventually reluctantly decides on the new name of Steph. Lost then offers to let Steph stay at his house. Have the rest of the story be about the two becoming surrogate siblings while Steph struggles to adapt to being catcalled and having female emotions and periods. Have 5 mind bogglingly long chapters. Do not introduce the characters or settings. Have Steven talk like a standard young adult. Have Lost be very casual and chill, treating Steven like a younger sibling. Have plenty of dialogue. Do not include graphic content or content that would make it innapropriate.
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 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 GitHub issue title of an Android app, aiming to categorize the issues into one or multiple 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 GitHub issue relate to a bug report or feature request or other?
issue: Subtitles: Set as default for all videos not saved | Kodi 18.9 / Kodi 19 with tvheadend'
intention: '
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 une sauce d’accompagnement.

    json
    {"category":"sauce","title":"Chipotle mayonnaise A creamy, salmon-colored mayonnaise or dip","ingredients":"For the recipe : flaxseed eggs,salt,ground chipotle chile powder,garlic cloves, minced,fresh lime juice,grapeseed oil,organic canola oil","instructions":"In a working glass or the container for your immersion blender, combine the flaxseed eggs, salt, chipotle powder, garlic, and lime juice. Pulse four or five times to mix the ingredients.\nIn a separate measuring cup with a spout, combine the oils.\nWith the blender running, slowly drizzle a few drops of oil into the container. Pouring gradually will enhance the emulsification process, creating a creamy texture.\nContinue blending and adding the oil in a slow stream until fully incorporated. If the oil accumulates on top, move your immersion blender up and down or pause the oil addition until it blends in.\nAfter mixing, cover and refrigerate for up to a week. The mayonnaise will thicken as it chills.","region":"MX"}
C. Get the Long Binary Number
time limit per test1 second
memory limit per test256 megabytes
Consider a binary number x
.Define c0(x)
 as the number of 0
 in x
,c1(x)
 as the number of 1
 in x
.

For example,x=10100
,we can get c0(x)=3,c1(x)=2
.

Now you're given a binary number y
(without leading zero) of length n
 and an integer k
.Your task is find the smallest binary number x
(without leading zero),which satisfies:

y≤x
;
c0(x)−c1(x)=k
.
Input
The first line of input will contain a single integer t(1≤t≤105)
, denoting the number of test cases.

Each test case consists of two line of input.

The first line contains two integers n,k(1≤n≤105,−105≤k≤105)
.

The second line contains a binary number y
(without leading zero) of length n
.

The sum of n,|k|
 over all test cases will not exceed 4∗105
.

Output
For each test case,output on a new line — the smallest binary number x
(without leading zero),which satisfies:

y≤x
;
c0(x)−c1(x)=k
.
Example
InputСкопировать
5
1 -1
0
6 -4
110100
6 1
100000
7 1
1110000
10 -2
1011010111
OutputСкопировать
1
110111
1000011
1110000
1011011001 solve in c++
clang is unable to create an executable file.
If clang is a cross-compiler, use the --enable-cross-compile option.
Only do this if you know what cross compiling means.
C compiler test failed.

If you think configure made a mistake, make sure you are using the latest
version from Git.  If the latest version fails, report the problem to the
<PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> mailing list or IRC #ffmpeg on irc.libera.chat.
Include the log file "ffbuild/config.log" produced by configure as this will help
solve the problem.
-Retrieve all URLs of a Twitter user's tweets.
-Upload all tweet URLs to the Wayback Machine for archiving.
-For each tweet:
  -Retrieve the Wayback Machine URL.
  -Extract tweet text.
  -Download any images associated with the tweet.
  -Take a screenshot of the tweet.
  -Generate a JSON file listing the tweet details.
-Sort all tweets by date.
-For each tweet URL:
  -Extract the tweet ID.
-Utilize the GitHub project "DocNow/tweet-viewer":
  -Use the tweet IDs to fetch the tweets from Twitter's API.
  -Display all tweets in chronological order.
  -Present them on a single page with the appearance of Twitter.
  -Example: https://tweet-viewer.vercel.app/
-Take a user's tweets and upload them to the Wayback Machine.
-Retrieve all URLs for that user on the Wayback Machine, including deleted tweets.
-Create an offline archive with the information retrieved from the Wayback Machine.
-Create an online archive version for each particular user.
-Ensure the online archive version has a similar appearance to that of Twitter.
What do you think?

-https://github.com/DocNow/tweet-viewer

-https://github.com/yusuf-yldrm/Tweet-Viewer
-https://tweet-viewer.vercel.app/
Create a communication to say which email is for which cluster and it is mandatory to create youyr ticket where neccesary by the process below
Lesson 6: Discussion - Chapter 6 factfulness hans roling: The Generalization Instinct
No unread replies.No replies.
apartment complex

In Chapters 5 and 6, Rosling explores how misconceptions and stereotypes affect the way we view the world and the people living in it. In these chapters, we are provided with some methods for controlling the Generalization Instinct. For example, Rosling reminds us of the importance of comparing numbers and closely examining the language used to discuss numbers, especially the term "majority." He urges us to look at differences and similarities within and across groups of people.

One tool that he mentions is Dollar Street, a website that collects photos and data from homes and families across the globe. You can see the website here.Links to an external site.

For this discussion, in 250 words:

Explore and Explain: Go to the Dollar Street website and look at the various search criteria. You can search "kitchens" or "backyards" or any number of items. You can also narrow your search by income, country, or continent. Try different searches and look at the photos. You can also get more information about the families and households whose homes are shown. What similarities do you observe across groups? Within groups? What surprised you or intrigued you? What conclusions can you draw? How do these photos compare to your perceptions of life in these countries and continents? Try to be as specific as you can.
For example, a photo of a kitchen in China looks very similar to one in India. However, the household in India has a monthly income of $607 and a household in China has one of $10,098. This seems noteworthy and leads to the conclusion that it is more expensive to live in China or that the family chooses to live modestly. Both kitchens feature hot plates instead of actual stoves and both kitchens contain spices for cooking. The Chinese kitchen has other smaller appliances, as well. These are the types of comparisons that you can describe and expand upon in your post.
import os
import requests

request = requests.post(
    'https://api.bfl.ml/v1/flux-pro-1.1',
    headers={
        'accept': 'application/json',
        'x-key': os.environ.get("BFL_API_KEY"),
        'Content-Type': 'application/json',
    },
    json={
        'prompt': 'A cat on its back legs running like a human is holding a big silver fish with its arms. The cat is running away from the shop owner and has a panicked look on his face. The scene is situated in a crowded market.',
        'width': 1024,
        'height': 768,
    },
).json()
print(request)
request_id = request["id"]

import time

while True:
    time.sleep(0.5)
    result = requests.get(
        'https://api.bfl.ml/v1/get_result',
        headers={
            'accept': 'application/json',
            'x-key': os.environ.get("BFL_API_KEY"),
        },
        params={
            'id': request_id,
        },
    ).json()
    if result["status"] == "Ready":
        print(f"Result: {result['result']['sample']}")
        break
    else:
        print(f"Status: {result['status']}")

перепиши на node.js
write a script of  an episode of kitchen nightmares where gordon ramsay looks at a resturant. in the middle of his visit, you (jake) who is an owner, admits to ramsay that you are struggling with being an owner and chef at the same time. you say to ramsay that he loves being an owner, but he also loves cooking. you ask ramsay what should you do. gordon is shocked that he has never seen an owner who is not only always honest to everyone, but who is struggling between two jobs.
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 operations and performance are materially connected to worldwide economic conditions. Because carbon black is used in a diverse group of end products, demand for carbon black has historically been related to real gross domestic product (“GDP”) and general global economic conditions. In particular, a large part of our sales has direct exposure to the cyclical automotive industry and, to a lesser extent, the construction industry. As a result, certain parts of our business experience a level of cyclicality. The nature of our business and our large fixed asset base make it difficult to rapidly adjust our fixed costs downward when demand for our products declines, which could materially affect our profitability. Global and regional economic downturns have in the past, and may in the future, reduce demand for our products, which have decreased and would decrease our revenue, and could have a material adverse effect on our business, financial condition, results of operations and cash flows. In periods with significant market turmoil and tightened credit availability, we could experience difficulties in accounts receivable collections, pricing pressure and reduced global or local business activity.
Assistant:
"Please advise about this" paraphrase this text message
[there would be dialogue in this story:]

(It all began in Telogrus Rift. Two void elf parents - Aelarion and Seraphina - were getting a nursery prepared for their daughter - who they've named "Sayori". Sayori was telepathic - and was communicating telepathically with her parents and the other void elves, while at the same time Elara, her twin sister who the parents completely forgot about for the past 5 months, was telepathically arguing with Sayori.)