agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Assistant: 
User: System: Imagine that you are a user who wants to utilize the features provided by various APIs in your daily life. Your task is to come up with realistic scenarios for using these APIs and express them as natural language instructions, as if you were asking a friend or assistant for help.
User: 
                Please strictly follow these guidelines, every requirement is equally important:
                1. The instructions should be 1 to 2 sentences long. Use a mix of interrogative sentences, first-person statements, imperative sentences, and other structures that convey a request. Aim for diversity in your instructions.
                2. Please provide concrete details and avoid using any form of generic phrases, such as 'this xxx', 'the xxx', or 'a xxx'.
                3. Your instructions should only involve the features provided by these APIs.
                4. Generate 10 diverse instructions.
                5. Use specific nouns and real-world examples from various domains, such as entertainment, sports, or technology.
                6. Do not mention the API's name in your instructions.
                7. Ensure diversity in language by combining questions with imperative statements and other structures that convey a request.
                8. The instructions should be in the language of the country attribute in the provided API information.
                9. The generated problem must strictly follow the API's parameter information.
                10. If country is Global, please generate 10 instructions in English.

                Here is the API information:
                {'country': 'Indonesia', 'tool_name': 'Cek ID PLN PASCA DAN PRA BAYAR', 'api_list': {'name': 'Get Data ID Pelanggan Tagihan PLN / PASCA BAYAR', 'url': 'https://cek-id-pln-pasca-dan-pra-bayar.p.rapidapi.com/plnpostpaid/{id}', 'description': '获取PLN后付费客户的账单数据。需要在表单中输入PLN ID。', 'method': 'GET', 'required_parameters': [], 'optional_parameters': [{'name': 'id', 'type': 'string', 'description': 'PLN客户的ID', 'default': '532411286263'}], 'statuscode': '200', 'schema': {}}}
                Please generate the question in the language of the specified country.
                your response:
Assistant:
Assistant:
Assistant: Hello! How can i help you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
 قم بإعادة صياغة النص باللغة العربية الفصحى، ولكن بطريقة أكثر رسمية. (ar).
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
تشغيل وايقاف وضع الطيران
Assistant:
(In the main Azur Lane base…)

Akashi: “Phew! All sorted out. Hopefully no more accidents, nyaa-”

Bismarck: (bursting through the door) “Guten Tag, my fellow shipgirl!”

Akashi: “AAH!!! Bismarck! Can you please stop blasting into my shop like that?! You scared me half to death, nyaa!”

Bismarck: “Apologies, Akashi. I did not mean to startle you.”

Akashi: “It’s alright, just try to be a little quieter next time, okay?”

Bismarck: “Understood. By the way, have you seen Belfast or Essex?”
std::optional<std::string> ReadFile(std::string_view path)
{
    if (!std::filesystem::exists(path))
    {
        return std::nullopt;
    }

    std::ifstream file(path.data());
    if (!file.is_open())
    {
        return std::nullopt;
    }

    std::stringstream stream;
    stream << file.rdbuf();
    return stream.str();
}

Will this function return the bytes of a given file ?
Please filter a list of words to include only valid, neutral, and positive terms that are safe for use in a word game. Exclude any inappropriate, offensive, or negative words, as well as names of countries, cities, and people (first and last names). Correct any spelling errors and lowercase. Return the results in a JSON array with only the filtered words. Source data: [falchion, falco, faldstool, fallacies, fallacious, fallaciousness, fallacy, fallboard, fallout, falsehood, falstaffian, familie, familist, familistere, familistery, famotidine, famulus, fanaloka, fano, fanon, fargo, fari, farmyard, faroese, fathead, fatuis, fatuity, fatuous, fatuum, faubourg]
System: You are an expert Named Entity Recognition (NER) system. Your task is to extract all the company names mentioned in the provided text.
Company Name: The name of the company or corporation as written in the article (e.g., "Apple Inc.", "Microsoft").
Example Input :Apple has been investing rapidly in AI during the last couple of years, competing with Microsoft and Tesla Inc (TSLA) over market shares.
Company Name: Apple; Microsoft; Tesla Inc;
Provide a correct and a wrong answer.
User: There's an old market saying "Sell in May and go away." Traders have been citing this cliché for years, and for good reason. T he S&P 500 dramatically underperforms during the months of May through October — when looking at data going back to World War II — a ccording to Sam Stovall, chief equity strategist at S&P/Capital IQ. That's the story for stocks, but in today's market, there are other assets to avoid in the coming months as well. Here's a look at four asset classes investors across the market are selling right now: 1. Sell utilities stocks. That's what Jeremy Hill at Old Blackheath is advising. He's using the strong run in the utilities sector to get out of the sector. One of his trades is to short the Utilities Select Sector Spyder, ticker XLU. That's one of the main ETFs that tracks the sector. "I believe that utilities are overvalued as a bond proxy and safety trade," Hill said. 2. Sell 10-Year Treasury notes. That's what Lord Abbett Fixed Income Strategist Zane Brown recommends. He thinks that there has been a lot of worry about the deepening crisis in Ukraine, as well as the prospects for stronger
Assistant:
Congenial Work Environment for Women: Key to Organisational Success 

Write an artical for 3500 words
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Wellness
How to Get Shredded the Right Way
Dropping body fat can be a long and perilous process. Instead of relying on shortcuts, chemicals, and crash diets, why not do it correctly?
SMART  ORDER ROUTING
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Attack on Titan S01E14 480p x264 AMZN WEB-DL Multi Audio ESub.mkv
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:   A top aide to Treasury Secretary Steven Mnuchin flew on billionaire investor Nelson Peltz's jet. The Treasury is currently working on a tax plan that could affect Peltz and other wealthy hedge-fund managers heavily.  The revelation comes amid broader questions about the Trump administration's use 
Assistant:
System: You are an accounting expert. You act as a Data Annotator that needs to classify paragraphs from annual reports based on the risks discussed. Here is a list of risk often discussed but you can provide others. 

Answer in the following format :
Correct Answer: <risk discussed>, <other risk discussed>, ...
Wrong Answer: <risk not discussed>, <other risk not discussed>, ...
User: To increase strategic focus and operational efficiency we have implemented restructuring programs. In fiscal 2019, we implemented a cost restructuring program, the primary element of which was staff reductions across all of our functions and geographic areas. In fiscal 2020, we continued to streamline our operations and closed our service organizations in Ireland and the Netherlands for which we realized annualized costs savings of $6.0 million. In fiscal 2021, we reduced our headcount across all departments in response to the COVID-19 pandemic for which we expect additional annualized cost savings of $7.6 million. We also transferred our technical support services to our Poland location in fiscal 2021 in an effort to further reduce cost. As a result of these restructuring efforts, our total number of employees significantly decreased. We may incur additional restructuring costs or not realize the expected benefits of these new initiatives. Further, we could experience delays, business disruptions, decreased productivity, unanticipated employee turnover and increased litigation-related costs in connection with past and future restructuring and other efficiency improvement activities, and there can be no assurance that our estimates of the savings achievable by restructuring will be realized. As a result, our restructuring and our related cost reduction activities could have an adverse impact on our financial condition or results of operations.
Let's give a correct and a wrong answer:
Assistant:
Hi, you busy?
Using Antigone, from Rivers and Tides, and Sonnet to Orpheus, write a 500 word essay making a CLAIM about the CONNECTIONS between the texts, supporting with evidence from each
Hey, this is a Tunisian dialect text I want you to translate to English.
Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

إيه منهم منهم الكوبل توانسة امرا وراجل خلاوا بيبي بخمسة شهر
write something about why everyone should.go vegan
generate more comprehensive details and examples on, - Course Structure and How to Get the Most Out of It, minimalist tone
make me 10 male names and 10 female names with only the first name and the initial of the last name make sure the first letter of the first name and the last
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
examples:

review: really disappointed with your customer services team. Ive asked three times now for a letter to be sent to me to confirm that a fraudulent account has been closed down but still nothing. Ask to speak to managers but theyre always in a meeting. #fraud #CustomerExperience
intention: bug report
review: I don't need a dm. Why don't your stores carry what I need for my phone?
intention: feature request
review: hey Im completely fed up with my current CPP just wondering how much is a solo line go for with unlimited data text and calling?
intention: other
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
examples:

review: really disappointed with your customer services team. Ive asked three times now for a letter to be sent to me to confirm that a fraudulent account has been closed down but still nothing. Ask to speak to managers but theyre always in a meeting. #fraud #CustomerExperience
intention: bug report
review: I don't need a dm. Why don't your stores carry what I need for my phone?
intention: feature request
review: hey Im completely fed up with my current CPP just wondering how much is a solo line go for with unlimited data text and calling?
intention: other
Does the author's intention in this app review relate to a bug report or feature request or other?
review: why does my internet speed slow or lag behind when Im in an overly crowded area? Seriously'
intention: '
Assistant:
It seems like there was an issue with the input you provided. If you could clarify or shorten your request, I'd be more than happy to help you out! Just let me know what you need. 😊
Translate

"神田財務官 為替介入の有無明らかにせず　一気に円高進む場面も ｜TBS NEWS DIG"
Assistant: Hello! How are you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
تصحيح الأخطاء باستخدام قواعد الإملاء القياسية للهجات المحلية.
 اكتب لي هالنص باللهجة الفلسطينية. (ar-PS).
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
الله يعطيك العافيه يا اخي
Assistant:
What was that bizarre transitional phase between Fox Kids and Disney XD
User: what is future covariates?

from darts.datasets import AirPassengersDataset
from darts.models import KalmanForecaster
from darts.utils.timeseries_generation import datetime_attribute_timeseries
series = AirPassengersDataset().load()
# optionally, use some future covariates; e.g. the value of the month encoded as a sine and cosine series
future_cov = datetime_attribute_timeseries(series, "month", cyclic=True, add_length=6)
# increasing the size of the state vector
model = KalmanForecaster(dim_x=12)
model.fit(series, future_covariates=future_cov)
pred = model.predict(6, future_covariates=future_cov)
pred.values()
array([[474.40680728],
       [440.51801726],
       [461.94512461],
       [494.42090089],
       [528.6436328 ],
       [590.30647185]])
Assistant: In time series forecasting, future covariates (also known as exogenous variables or external regressors) are additional variables that you believe might have an impact on the variable you're trying to predict. These covariates are provided as inputs to the forecasting model alongside the main time series data to potentially improve the model's accuracy.

For the "AirPassengers" dataset and the KalmanForecaster model you are using, you have chosen the "month" as a future covariate, encoded as sine and cosine components. This technique is common when dealing with cyclic or periodic patterns, such as seasonal effects. By encoding the month in this way, you're essentially providing the model with information about the cyclic nature of the data, which might help it make more informed forecasts.

Here's a breakdown of what's happening in your code:

1. **Data Loading**: You load the AirPassengers time series dataset, which contains monthly passenger numbers for an airline.

2. **Covariate Generation**: Use the `datetime_attribute_timeseries` utility to create a time series of cyclic covariates corresponding to months, with sine and cosine transformations. These transformations help in capturing the cyclic nature and allow the model to understand the repeating patterns (e.g., seasonality).

3. **Model Configuration**: A `KalmanForecaster` model is initialized with an increased state dimension (`dim_x=12`). This state vector's dimension influences how much past information the model can incorporate.

4. **Model Fitting and Prediction**: Fit the model to the data while providing both the primary time series and the future covariates. Then, predict future values by using these covariates to make better forecasts.

In summary, future covariates like the cyclic month representation can improve forecast accuracy by incorporating periodic effects into the modeling process.
User: can i use future covariate such as weather component like weather?
Assistant:
nlohmann json [{"life":1425,"class_id":1001,"passiveSkillId":11001,"defence":600,"type":101},{"life":1800,"class_id":1002,"passiveSkillId":12001,"defence":455,"type":101},{"life":2000,"class_id":1003,"passiveSkillId":13001,"defence":400,"type":101}] 获取里面的class_id值
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: In connection with licensing content, we typically enter into multi-year commitments with content providers. We also enter into multi-year commitments for content that we produce, either directly or through third parties, including elements associated with these productions such as non-cancellable commitments under talent agreements. The payment terms of these agreements are not tied to usage or the size of our user base but may be determined by costs of production or tied to such factors as titles licensed. Such commitments, to the extent estimable under accounting standards, are included in Note 13 in the accompanying notes to our consolidated financial statements included in Part II, Item 8, “Financial Statements and Supplementary Data” of this Annual Report on Form 10-K. Given the multiple-year duration and largely fixed cost nature of content commitments, if user acquisition and retention do not meet our expectations, our margins may be adversely impacted. Payment terms for certain content commitments, such as content we directly produce, will typically require more up-front cash payments than other content licenses or arrangements whereby we do not cash flow the production of such content. To the extent user and/or revenue growth do not meet our expectations, our liquidity and results of operations could be adversely affected as a result of content commitments and accelerated payment requirements of certain agreements. In addition, the long-term and fixed cost nature of our content commitments may limit our flexibility in planning for or reacting to changes in our business and the markets in which we operate. If we license and/or produce content that is not favorably received by consumers in a territory, or is unable to be shown in a territory, acquisition and retention may be adversely impacted and given the long-term and fixed cost nature of our content commitments, we may not be able to adjust our content offering quickly and our results of operation may be adversely impacted._
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:

[Ion transport in nasal and paranasal sinus mucosa in mucoviscidosis and chronic sinusitis]. Cystic fibrosis (CF) is the most commonly inherited disease in Caucasians and is caused by a mutation in the gene encoding a membrane transport protein. This cystic fibrosis transmembrane conductance regulator (CFTR) is thought to be an apical Cl- channel activated by intracellular cAMP. Most recent findings suggest that CFTR is more than a pure Cl- channel and might be involved in the regulation of other transport systems. In the present study we show that CFTR as a Cl- channel plays only a minor role in primary cultured human nasal epithelium derived from non-CF and CF patients. These findings are especially of interest for non-CF human nasal epithelia in which CFTR is correctly inserted. In both tissues Cl- secretion is negligible as compared with Na+ absorption. We confirm and expand our previous observations that Na+ absorption in human nasal epithelium is the dominant ion transport process and that Cl- secretion is detectable in both CF and non-CF tissue. Moreover, we show that cAMP and ATP were not able to stimulate any silent Cl- channels in CF or non-CF human nasal epithelial cells. We further give evidence that in human nasal CF and non-CF epithelium Na+ absorption is mediated by epithelial Na+ channels (ENaC) that are either different from those of other epithelia or which exhibit altered regulation. These differences between Na+ channels of human nasal epithelium and "classical" epithelial Na+ channels include lack of activation by the intracellular second messenger cAMP and the steroid hormone aldosterone. We show further that human nasal Na+ channels are inhibited by Cl- channel blockers and exhibit a different pharmacology towards common Na+ channel blockers.