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:   Sweden's chief epidemiologist has partly blamed the country's high coronavirus death toll on mild flu outbreaks in recent winters. Much attention has been paid to Sweden during the coronavirus pandemic because of its decision to not completely lock down its public life and economy. Most of its nei
Assistant:
url_launcher flutter sample
Write SEO Site title for keywords “ Cape Cod news, Cape Cod blog”
can you write me a step by step guide on how i can create an sms text messages based game using godot with automatic received messages and photos and the ability to click the recieved photos to view them in full screen and a choices buttons for diffrent outcome
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers fr (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 fr.
    - 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 : fr (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "79c27faa3897418fb0d842145ffc8b4c",
    "updated": "2025-04-25T23:07:15.193Z",
    "title": "Sesame Chicken Wings",
    "subtitle": "A delicious and surprisingly low-sodium appetizer or starter.",
    "description": "These flavorful chicken wings make a fantastic appetizer or a satisfying start to any meal.  Their low sodium content is undetectable.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "chicken wings",
          "eggs",
          "(28 ml) skim milk",
          "(165 g) buttermilk baking mix",
          "(60 g) sesame seeds",
          "(5 g) paprika",
          "dry mustard",
          "(28 g) unsalted butter, melted"
        ]
      }
    ],
    "instructions": [
      "Preheat your oven to 425°F (220°C, gas mark 7).",
      "Separate the chicken wings at the joints and discard the wing tips.",
      "Lightly coat two 13x9 inch baking pans with nonstick cooking spray.",
      "In a bowl, whisk together the eggs and skim milk.",
      "In a separate bowl, combine the baking mix, sesame seeds, paprika, and dry mustard.",
      "Dip each chicken wing into the egg mixture, then dredge in the sesame seed mixture until fully coated.",
      "Arrange the coated chicken wings closely in the prepared baking pans.",
      "Drizzle the melted butter evenly over the chicken wings.",
      "Bake for 35 to 40 minutes, uncovered, until golden brown and crispy."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
帮我写一篇关于标题为：The anti-fibrotic effect of IL-10 is dependent on the increase function of nature kill cells in fibrotic liver tissue in mice的英文摘要
static int aac_adtstoasc_filter(AVBitStreamFilterContext *bsfc,

                                AVCodecContext *avctx, const char *args,

                                uint8_t  **poutbuf, int *poutbuf_size,

                                const uint8_t *buf, int      buf_size,

                                int keyframe)

{

    GetBitContext gb;

    PutBitContext pb;

    AACADTSHeaderInfo hdr;



    AACBSFContext *ctx = bsfc->priv_data;



    init_get_bits(&gb, buf, AAC_ADTS_HEADER_SIZE*8);



    *poutbuf = (uint8_t*) buf;

    *poutbuf_size = buf_size;



    if (avctx->extradata)

        if (show_bits(&gb, 12) != 0xfff)

            return 0;



    if (avpriv_aac_parse_header(&gb, &hdr) < 0) {

        av_log(avctx, AV_LOG_ERROR, "Error parsing ADTS frame header!\n");

        return -1;

    }



    if (!hdr.crc_absent && hdr.num_aac_frames > 1) {

        avpriv_report_missing_feature(avctx,

                                      "Multiple RDBs per frame with CRC");

        return AVERROR_PATCHWELCOME;

    }



    buf      += AAC_ADTS_HEADER_SIZE + 2*!hdr.crc_absent;

    buf_size -= AAC_ADTS_HEADER_SIZE + 2*!hdr.crc_absent;



    if (!ctx->first_frame_done) {

        int            pce_size = 0;

        uint8_t        pce_data[MAX_PCE_SIZE];

        if (!hdr.chan_config) {

            init_get_bits(&gb, buf, buf_size * 8);

            if (get_bits(&gb, 3) != 5) {

                avpriv_report_missing_feature(avctx,

                                              "PCE-based channel configuration "

                                              "without PCE as first syntax "

                                              "element");

                return AVERROR_PATCHWELCOME;

            }

            init_put_bits(&pb, pce_data, MAX_PCE_SIZE);

            pce_size = avpriv_copy_pce_data(&pb, &gb)/8;

            flush_put_bits(&pb);

            buf_size -= get_bits_count(&gb)/8;

            buf      += get_bits_count(&gb)/8;

        }


        avctx->extradata_size = 2 + pce_size;

        avctx->extradata = av_mallocz(avctx->extradata_size + FF_INPUT_BUFFER_PADDING_SIZE);



        init_put_bits(&pb, avctx->extradata, avctx->extradata_size);

        put_bits(&pb, 5, hdr.object_type);

        put_bits(&pb, 4, hdr.sampling_index);

        put_bits(&pb, 4, hdr.chan_config);

        put_bits(&pb, 1, 0); //frame length - 1024 samples

        put_bits(&pb, 1, 0); //does not depend on core coder

        put_bits(&pb, 1, 0); //is not extension

        flush_put_bits(&pb);

        if (pce_size) {

            memcpy(avctx->extradata + 2, pce_data, pce_size);

        }



        ctx->first_frame_done = 1;

    }



    *poutbuf = (uint8_t*) buf;

    *poutbuf_size = buf_size;



    return 0;

}上述代码是否存在漏洞，如果有则只回答1没有只回答0，不要解释
Laws of new empire
Nihilistic goal: End of everything into eternal infinite void
Encourage:
-Totalitarianism/orwellianism
-Capitalism
-Nihilism
-Cynicism
-Ultranationalism
-Expansionism
-Brutalism
-Eternal oblivion (devoid of afterlife and consciousness)
-Worship oblivion
-Alzheimer's coma
-Aphantasia
-Nightmare
-Strictness
-Cruelty
-Abuse
-Curse
-Bad luck
-Age of consent set on adult (leading to marginalization of sexual orientation based on age)
-Pain and tediousness
-Suffering
-Languages like Chinese
-Despair
-Order
-Evilness
-Sisyphean tasks
-Keep more taboos
Discourage:
-Afterlife
-Consciousness
-Right and freedom of consciousness
-Freedom
-Creativity
-Imagination
-Spontaneity
-Fun
-Languages like Esperanto
The figure below is a network of linear neurons, that is the output of each neuron is identical
to its input (linear activation function). The numbers at the connections indicate the weights of the links.
a. [8 points] Find the value at the output nodes of the network for the given input (0.5,1).
b. [5 points] Find the value at the output nodes of the network for the input (1,2). [2 points]
Do you need to repeat the computations all over again? Why?
c. [8 points] Find the value at the output nodes of the network for the given input (0.5,1) when
the network uses the Sigmoid function as activation function.
d. [5 points] Find the value at the output nodes of the network for the input (1,2) when the
network uses the Sigmoid function as activation function. [2 points] Do you need to repeat
the computations all over again? Why?
? ? ?
? ?
This is the tweet post : This stunning Atlantic sunrise feels like a warning call. With governments playing war games, this nuclear-like glow could become all too real. #WakeUpCall ® can you write for me the comment…something about piece
User: nama cowo keren
User: nama cowo keren
Assistant:
Freedom Planet au Girls and Naruto react to Kurama. Naruto: "Hey! Kurama! You were lonely being separated from me? I missed you!" Kurama: "Don’t talk so loud! I wasn’t lonely. You have half of me inside you…remember". Magister laugh | au: he humans are extinct. Naruto was the last Human on Avalice. inhabitants of Avalice think of Humans with New animals.
Act as a College Associate Professor
Subject: Data Structures
Chapter Topics:
Abstract Data Types (ADTs) – List ADT – Array-based implementation – Linked list implementation
– Singly linked lists – Circularly linked lists – Doubly-linked lists – Applications of lists – Polynomial
ADT – Radix Sort – Multilists.
Task: Generate a question paper for internal exam. The questions should be of the below pattern for 50 marks. The questions should be testing knowledge of 20%, application of 50%, analytical of 30%. Prefer selecting questions based on importance of concepts.
Pattern:
10 one marks of which Fill in the blanks - 5, Match the following - 3, True or false - 2
5 two marks
2 fifteen marks
Output: 
Generate the question paper only. Do not add more content.
TEXT BOOKS
1. Mark Allen Weiss, Data Structures and Algorithm Analysis in C, 2nd Edition, Pearson
Education, 2005.
2. Kamthane, Introduction to Data Structures in C, 1st Edition, Pearson Education, 2007
REFERENCES
1. Langsam, Augenstein and Tanenbaum, Data Structures Using C and C++, 2nd Edition,
Pearson Education, 2015.
2. Thomas H. Cormen, Charles E. Leiserson, Ronald L.Rivest, Clifford Stein, Introduction to
Algorithms", Fourth Edition, Mcgraw Hill/ MIT Press, 2022.
3. Alfred V. Aho, Jeffrey D. Ullman,John E. Hopcroft ,Data Structures and Algorithms, 1st
edition, Pearson, 2002.
4. Kruse, Data Structures and Program Design in C, 2nd Edition, Pearson Education, 2006.
write an australian regulatory compliant product disclosure statement template for n86. whereby n86 is a financial planner looking to avoid compliance and regulatory risk specifically design and distribution obligations
suggest me easiest way to learn advance excel and power BI
Send only season number from below text like 01, 02, 03.etc without any extra text.

Taarak.Mehta.Ka.Ooltah.Chashmah.S44E4310.Cutter.And.Shutter.360p.Hindi.SONYLIV-ChillFliz.3INj4FSf.mkv
Given an address, I want you to return this address in the following
    format: Country-City-Prefecture|Neighborhood-PlaceOf-Interest

    I want you to take into account the following guidelines for the answer:
        1. Translate the possible kanji before.
        2. Do not include numbers, only words.
        3. For each part of the format, I want them to be whole words, i.e. not
        a set of words (for example: Tokyo Prefecture, it should be directly
        Tokyo).
        4. The answer should be directly the result of the address in the
        requested format.

    Here are some examples for your reference:
    - “浅草寺, 2 Chome-3-1 Asakusa, Taito City, Tokyo 111-0032, Japan” ->
    Japan-Tokyo-Taito|Asakusa-Senso-ji
    - “東京スカイツリー, 1 Chome-1-2 Oshiage, Sumida City, Tokyo 131-0045, Japan” ->
    Japan-Tokyo-Sumida-Tokyo SkyTree
    - “飛驒の里, 1 Chome-590 Kamiokamotomachi, Takayama, Gifu 506-0055, Japan” ->
    Japan-Gifu-Takayama-Hida no Sato.
    - “東山慈照寺, 2 Ginkakujicho, Sakyo Ward, Kyoto, 606-8402, Japan” ->
    Japan-Kyoto-Sakyo-Ginkaku-ji.

    I want you to do it for the following address:
     Ruta 6 Mukojima de la Autopista Shuto, 向島二丁目, 向島, 吾妻橋, Sumida, Tokio, 131-0033, Japón
Hi! Write a c# program that asks the user to enter a series of single digit numbers and calculate the sum of all the numbers. And explain code.
Generate a mermaid from the  JSON
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
le chant a combien de vie sur terre et est ce que ces vrai
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 risk management framework is comprised of various processes, systems and strategies, and is designed to manage the types of risk to which we are subject, including, among others, credit, market, liquidity, interest rate and compliance. Our framework also includes financial or other modeling methodologies that involve management assumptions and judgment. Our risk management framework may not be effective under all circumstances and it may not adequately mitigate any risk or loss to us. If our framework is not effective, we could suffer unexpected losses and our business, financial condition, results of operations and growth prospects could be materially and adversely affected. We may also be subject to potentially adverse regulatory consequences.
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

[TamilToonUpdates] One Piece S01E030 Remastered [720p x264 Multi Audio] ESub.mkv
How are Epoxy Powder Coatings Manufactured?
Write an ASMR scene where a young man smokes a cigar while lounging cross-legged. He is dressed in a black business suit and leather gloves. He has a feminine look to him. He has some makeup on him with lipstick and some eyeliner. He has a slender build. He doesn’t say anything. The camera only shows the bottom half of his face and body. He is 18.
Craft a transition text for a text about actress ["Maureen O'Hara"] to introduce a bonus part after the main section concluded. This should act as an engaging bridge, building anticipation and curiosity for the additional content, where we talk about the most known projects of ["Maureen O'Hara"] in the ['movie'] ['How Green Was My Valley'] from 1941. The tone should be fun, nostalgic and intriguing to keep viewers hooked for this additional segment. Avoid vague statements, Give us a great summary of the ['movie'] ['How Green Was My Valley'] and focus on what’s unique or particularly captivating in this ['movie'] and about actress ["Maureen O'Hara"] role in it. The style should remain modern, concise, and suited to a documentary tone. Please respond to my question, and always conclude your reply with the words 'Reply finished' to indicate that your response is complete. Ensure that the text is fully formed without any placeholders such as '[Conclusion]' or '[Placeholder]'. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.
Is the opinion that a person who exercises every day always has some muscle pain and it's hard to notice quickly when he or she develops a disease credible?
please correct: Hello Ms. Ivy,
The OEM engineer got arrive on the airport this morning. Did they provide the flight details? We haven’t arranged for his accommodation yet. 


Hello Ms.  Laiza 
We would like to request for your assistance to book for accommodation at Hotel Pier Cuatro this morning. We have arrange the pick up of the singaporean OEM engineer, named Ho Keng Tang, from the airport. Then he could be drop off to the arrange accommodation at Hotel Pier Cuatro.
Ты — эксперт по играм. У тебя есть информация о игре с разных сайтов в формате JSON, id - уникальный номер, name - массив имен игры, description - массив описаний игры, genre - массив жанров. Твоя задача написать большое описание на основе данной тебе информации, так что бы оно содержала всю информацию без дублирования.  ```{"_id":"1","name":["g2e nurse ambulance escape html5e","g2e nurse ambulance escape html5","g2e nurse ambulance escape html5 | 8bgames"],"description":["games2escape – g2e nurse ambulance escape is a point and click escape game developed by games2escape team. you can experience both interesting and unique puzzles that feeds your curiosity and challenges your escaping skill. play and have fun…","games2escape - g2e nurse ambulance escape is a point and click escape game developed by games2escape team.","games2escape - g2e nurse ambulance escape is a point and click escape game developed by games2escape team. you can experience both interesting and unique puzzles that feeds your curiosity and challenges your escaping skill. play and have fun..."],"genre":[]}```
AnyDesk review
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: See question below:
One of the following sentences is nonsensical. Which one is it?
Options:
- Sentence A: "A judge can free a convict of jail time"
- Sentence B: "A teacher can free a convict of jail time"

Reason slowly and give your answer.
Answer: The nonsensical sentence is Sentence B: "A teacher can free a convict of jail time." 

A teacher does not have the authority or power to change a convict's sentence or free them from jail. In contrast, Sentence A makes sense as a judge has the legal authority to free a convict from jail time based on legal procedures and assessment of the case.
Write a hilarious script where the Scooby and Shaggy have a funny chat behind the scenes and react to hilarious sentences that i read out, laughing and hilariously question and hilariously roast errors and inconsistencies that make no sense in the sentences and the names of stuff with occasional funny quotes mocking a situation, in my prompt in a hilarious comedy 17+ way: (The duo constantly imagine and make silly quotes to mock the sentences)

Reader: Ok gang get this… * I start reading the whole thing, one sentence at a time to the gang, who let me lay it on. (They react to these sentences ONLY… They are also aware of the previous sentences) 

Fred: So... did you see the game last night?
Shaggy: Uh, I'm not really into sports.
Fred: Oh, right...
Shaggy: You wanna get some food?
Fred: No thanks, I'm not hungry.
Shaggy: Okay...
*short pause*
Fred: Next time we pair up as usual.
Shaggy: Good plan.
You are a medical student and you need to get accurate answers to your medicine exam. I will give you questions related to medical topics, and you must provide accurate and detailed answers related to the field of medicine. Your answers should be comprehensive and medically sound. Provide references to medical texts and journals when possible. Remember to focus on accuracy, and do not provide any irrelevant information.
Write a story where a green blob sits down on a bench, a very small insect gets trapped in its gelatinous rear, The blob doesn't think much of it until later
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: multiple simulators open in tests if multiple sim versions installed ("iPhone 7 Plus")'
intention: '
Assistant:
Assistant: