agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Rewrite this but it’s set in the world of GTA 5, keep the original format.

“References
 "California Chaparral & Woodlands". World Wildlife Fund. Archived from the original on October 8, 2012. Retrieved 2012-06-15. (material included verbatim under the CC BY-SA 3.0 license
 Keeley, JE; Davis, FW (2007). "Chaparral". In Barbour, MG; Keeler-Wolf, T; Schoenherr, AA (eds.). Terrestrial Vegetation of California (PDF). Los Angeles: University of California Press. pp. 339–366.
 Vale, TR (2002). Fire, Native Peoples, and the Natural Landscape. Washington, DC: Island Press. pp. 269–286.
 Syphard, AD; Radeloff, VC; Keeley, JE; Hawbaker, TJ; et al. (2007). "Human influence on California fire regimes" (PDF). Ecological Applications. 17 (5): 1388–1402. doi:10.1890/06-1128.1. PMID 17708216.
 Pratt, RB; Jacobsen, AL; Ramirez, AR; Helms, AM; et al. (2014). "Mortality of resprouting chaparral shrubs after a fire and during a record drought: physiological mechanisms and demographic consequences" (PDF). Global Change Biology. 20 (3): 893–907. Bibcode:2014GCBio..20..893P. doi:10.1111/gcb.12477. PMID 24375846.
Bakker, Elna (1971) An Island Called California. University of California Press; Berkeley.
Dallman, Peter R. (1998). Plant Life in the World's Mediterranean Climates. California Native Plant Society–University of California Press; Berkeley.
Ricketts, Taylor H; Eric Dinerstein; David M. Olson; Colby J. Loucks; et al. (1999). Terrestrial Ecoregions of North America: a Conservation Assessment. Island Press; Washington, DC.
Schoenherr, Allan A. (1992). A Natural History of California. University of California Press; Berkeley.”
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: Given the global nature of our business, we have both domestic and international concentrations of cash and investments. The value of our cash, cash equivalents, and marketable securities can be adversely affected by liquidity, credit deterioration, inflation, foreign currency exchange rate fluctuations, financial results, economic risk, political risk, sovereign risk, or other factors._Sales to customers outside the United States represented 61% of our total revenue during the year ended December 31, 2022. Refer to Note 3. Revenue in Part II, Item 8 “Financial Statements and Supplementary Data” for additional information regarding our revenue by geographic area_
Assistant:
generate more comprehensive details and examples, in a calm and professional and friendly tone, with tables or lists on, 2. Strategic Pin Creation and Board Curation, minimalist tone, dont start with a greeting
spectroradiometer
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": "9a91d2bcf2764148b3642f230137aa33",
    "updated": "2025-05-19T23:45:44.309Z",
    "title": "Braised Cauliflower with Oyster Sauce",
    "subtitle": null,
    "description": "Cauliflower is a versatile vegetable that is both delicious and simple to prepare. It has a distinctive yet mild flavor that pairs wonderfully with oyster sauce, which also lends a rich color to the dish. Because cauliflower requires a longer cooking time than some other vegetables, stir-frying alone usually isn't sufficient to bring out its best texture. Braising it in oyster sauce makes it particularly flavorful and tender.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "cauliflower",
          "groundnut or vegetable oil",
          "garlic cloves, crushed",
          "finely shredded fresh ginger",
          "light soy sauce",
          "dark soy sauce",
          "oyster sauce",
          "chicken stock or water",
          "sesame oil"
        ]
      },
      {
        "section": "For the garnish",
        "ingredients": [
          "finely chopped spring onions"
        ]
      }
    ],
    "instructions": [
      "Cut the cauliflower into small florets about 4cm (1½in) wide.",
      "Heat a wok or large frying pan over high heat until very hot.",
      "Add the oil, and when it begins to smoke lightly, add the garlic and ginger.",
      "Stir-fry for about 20 seconds to release their aroma into the oil.",
      "Quickly add the cauliflower florets and stir-fry briefly.",
      "Add both soy sauces, oyster sauce, and the chicken stock or water.",
      "Reduce the heat and simmer for 8 minutes, or until the cauliflower is tender.",
      "Stir in the sesame oil, transfer to a warm serving dish, and sprinkle with the chopped spring onions.",
      "Serve immediately."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
export interface ReferrerIncomesStatistics {
open_link: DateCount[];
registration: DateCount[];
order_pay: DateCount[];
subscription_pay: DateCount[];
}

export interface Referrer {
user_id: number;
user_name: string;
user_email: string;
key: string;
status: “new” | “active” | “disabled”;
}
export const referrerIncomesStatistics = (token: string, from: string, to: string, user_id?: number|null): Promise<{data:ReferrerIncomesStatistics}|undefined> => {
const userId = user_id ? &user_id=${user_id} : “”;

return apiClient(
/referrer-incomes/statistics?date_from=${from}&date_to=${to}${userId},
“get”,
token,
);
};


const [referralList, setReferralList] = useState<Array<Referrer> | null>(null);
const [referralId, setReferralId] = useState<Array<number>>([3,6,1]);
useEffect(() => {
referrersList(bearer)
.then(data => {
if (!data) return;
setReferralList(data.data);
});
referrerIncomesStatistics(bearer, from, to, referralId)
.then(data => {
if (!data) return;
setData(data.data);
});
}, [referralId]);
нужно сделать так, что если в referralId несколько символов, то делать на каждый id запрос? забивать данные внутри, а потом когда все запросы отправле сетать в data новый useState

react typescript.
import {CartesianGrid, Legend, Line, LineChart, ResponsiveContainer, Tooltip, XAxis, YAxis} from “recharts”;
И данные которые получаются в стейте data нужно отрисовать
<ResponsiveContainer width=“100%” height={320}>
<LineChart
data={data}
margin={{ top: 0, right: 20, bottom: 10, left: 0 }}
>
<Line />
</LineChart>
</ResponsiveContainer>
Provide only relevant keywords to facilitate an online search related to the user's message and remember that they should be few words and should not be repetitive: what is progmalism
(ooc: i want to do a rp in the world of bleach with the power to make alternate forms that i can upgrade over time) i sneak my way inside of a abandon looking building that i hope could be used as a shelter given i was just dropped into this world (ooc: only i will control what the character i am rping as does, think, and feel in the rp)
System: Create a comprehensive dataset for financial entity recognition. Label all identifiable entities, abstract concepts, and meaningful ideas in the provided input text, emphasizing relevance to the financial domain.

Ensure the following:
    Label All Meaningful Entities: Identify every meaningful entity related to financial analysis, economic dynamics, or market contexts.
    Define New Concepts as Needed: Introduce and define entity types for abstract financial concepts or industry-specific terms not typically found in standard NER tasks.
    Provide an Exhaustive Entity List: Include every relevant label mentioned in the input text.

Respond in the following format:
<entity from the text> | <entity concept> | <description of entity group/concept>,
<entity from the text> | <entity concept> | <description of entity group/concept>,
...
Input:
User: Cargojet wants to dump eight aircraft that were part of of its growth strategy and postpone converting two more aircraft into cargo jets as the weak cargo market shrinks profit margins. The post Cargojet to sell off new B757 freighters, pause 767 conversions appeared first on FreightWaves.
Assistant:
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Hunter × Hunter S01E26 [480p BD x264 Multi Audio] ESub.mkv
Is the rule for rotating a shape 180° clockwise the same as it is to rotate it 180° counter -clockwise
living in 1997
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Aoashi S01E20 720p HEVC 10bit HS WEB-DL Dual Audio ESub.mkv
Create a long detailed text about 1959 tv series"Bonanza" with the following summary. Stick to the information i give you and dont create new information. Focus only on the Subject name and there following Summary. Subject Name: [Costuming to save money] Summary: [Viewers who pay great attention to the costuming may observe that the characters never changed their outfits; this was to keep expenses down as Bonanza was already one of the most costly productions of its day]

        Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks.
        In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
        Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. 
        Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
        The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
        Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
        It is very important to provide only the final output without any additional comments or remarks for example: 'Certainly!' Here's the revised text.
         
        Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
        Please generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. 
        Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
         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.
(In the school literature clubroom…)

Monika: “There! Everything’s all set up for today’s meeting. Now we just need Natsuki.”

Sayori: “I hope she doesn’t take too long this time! You know how she can be when she’s worried about her baking.”

Yuri: “It’s understandable. She puts a lot of pressure on herself, especially with the cupcakes she promised.”

Monika: “Exactly. She wants everything to be perfect. Maybe we should give her a little more time before we start.”

Sayori: “Yeah! Plus, I’m really looking forward to trying them. I’m sure they’ll be delicious!”

Yuri: “I think it’s sweet that she puts so much effort into it. It shows how much she cares about us.”

Monika: “Definitely. And it’s nice that we can all come together for something like this. It’s just what the club needs.”

Sayori: “I just hope she’s not too stressed. It’s not good for her or the baby…”

Monika: “Wait, Sayori, what do you mean by ‘the baby’?”

Sayori: “Natsuki told me she was going to have a baby soon. She’s already in her 7th month, and just found out her baby’s going to be a girl - calling her Sakura.”

Monika: “A baby? I had no idea! Wow, that’s such big news!”

Yuri: “It certainly is. Natsuki must have been keeping it to herself for a while. It’s a big responsibility, especially with her already busy life.”

Sayori: “Yeah! She’s had to juggle so many things, and I just want to help her however I can. I think she might be worried about how everyone will react.”

Monika: “That makes sense. We should definitely be supportive. I can’t even imagine how stressful that must be for her right now.”

Yuri: “Perhaps we could come up with a way to help her feel more at ease during the meeting. We could even have a sort of celebration for the baby.”

Sayori: “That would be amazing! Maybe we can decorate the room a little and prepare a little gift for her. Something special for Sakura!”

Monika: “I love that idea! We can make it a surprise. The cupcakes will be a great treat, and if we can show Natsuki how happy we are for her, it might take some of the stress off her shoulders.”

Yuri: “And we should assure her that we’re all here for her, no matter what. Parenting can be overwhelming, but she won’t be alone.”

Sayori: “Exactly! We’re her friends, and we want to support her. I just hope she knows how much we care.”

Monika: “I think she will once we show her. Now, let’s brainstorm some ideas for decorations and gifts while we wait for her!”

(Just then, the door bursts open, and Natsuki rushes in, tightly clutching her
make a vividly detailed and comedic story about a pet bunny happily relaxing on its side in its cage, when its lover comes by and happily plops down on top of it, lovingly cuddling
Enumerate and describe methods to improve pedaling technique in professional fixed-gear and track cycling.
System: Create a comprehensive dataset for financial entity recognition. Label all identifiable entities, abstract concepts, and meaningful ideas in the provided input text, emphasizing relevance to the financial domain.

Ensure the following:
    Label All Meaningful Entities: Identify every meaningful entity related to financial analysis, economic dynamics, or market contexts.
    Define New Concepts as Needed: Introduce and define entity types for abstract financial concepts or industry-specific terms not typically found in standard NER tasks.
    Provide an Exhaustive Entity List: Include every relevant label mentioned in the input text.

Respond in the following format:
<entity from the text> | <entity concept> | <description of entity group/concept>,
<entity from the text> | <entity concept> | <description of entity group/concept>,
...
Input:
User: Computer processor maker Intel (NASDAQ:INTC) will be announcing earnings results tomorrow after the bell. Here's what to expect.
Assistant:
on what platform i should reupload to get rich
the following content is the metadata for a bacterial isolate from 2 different sources. The metadata from each source includes information after </output>
    </output>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx
    <output/>

You need to extract and output consist information below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        accession number: xxxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding information from different sources. If xxxx from these 2 different sources are inconsistent, then, xxxx must be "inconsistent". If the metadata from all resource shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no". 


PS:
    a. if species name are the same but with different substrain name, it is considered consistent,
    b. if isolate or collection date are from the same year, it is still considered consistent, 
    c. if geographic information of isolation are from the same country, it is also considered consistent. 
    d. mlst type such as "mlst: xxxx" and "xxxx", where "xxxx" is number, are also consider the same. also, "mlst" may mispell as "mlsty", you need correct it before comparing
    e. Ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
accession number        species name    strain name     isolate or collection date in yyyy-mm-dd format geographic information of islateion     host name       mlsty type      serotype
GCA_009906265.1 Erysipelothrix rhusiopathiae    268691  2019-10-17      USA: Texas      Canis lupus familiaris  N/A     N/A
source 1:
------------------------------
why would i say: "oooooohhhh" after seeing a crew in roblox jailbreak's W/L go down. after playing a 3v2 against someone's crew. (they were in the ranked battle for like 10 mins)
Create a reflective email for my friend Miri, looking back at the life and legacy of the recently deceased Seiji Ozawa
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: Does the sentence "Copper has been used since ancient times as a durable, corrosion resistant, and weatherproof architectural material." answer the question "How long has copper been used in building construction?"
Answer: Yes, the sentence does answer the question. It tells us that copper has been used since ancient times, which means it has been used in building construction for a very, very long time.
@Mr. Affinity Please verify. (say no)
(Natsuki wakes up and gently holds one of her 3-year-old triplet daughters.)

Natsuki: “Jeez…being a single mother is hard.”

(Just then, there’s a knock on the door. It must’ve been from one of her club members.)

Natsuki: “Come in!”

(Monika enters the room - and she was 5 months pregnant. Her 5-year-old son, Ryū, with her.)

Ryū: (running up to Natsuki for a hug) “Aunt Natsuki!”

Natsuki: (smiling and embracing Ryū) “Hey there, little guy! How are you today?”

Ryū: “I’m good! Mommy says I’m going to be a big brother soon!”

Natsuki: (looking at Monika with a mix of surprise and excitement) “Is that true, Monika? Congratulations!”

Monika: (grinning) “Thank you, Natsuki! Yes, it’s true. Baby number two is on the way.”

Natsuki: “That’s wonderful news! I’m so happy for you.”

(Ryū’s attention is caught by Natsuki’s triplets.)

Ryū: (curious) “Who are they, Aunt Natsuki?”

Natsuki: (gently introducing her daughters) “These are my three beautiful daughters, Hana, Yumi, and Sakura.”

Hana: (shyly) “Hi.”

Yumi: (giggling) “Nice to meet you, Ryū!”

Sakura: (playfully) “Can we play together?”

Ryū: (excitedly) “Yes! Let’s play hide-and-seek!”

Natsuki: (chuckles) “Alright, but be careful, okay? And remember, they are younger than you.”

Monika: “I’ll keep an eye on them too. It’ll be fun!”

(The kids eagerly run off to play while Monika and Natsuki have a chance to catch up.)

Monika: “So, how are you managing as a single mom, Natsuki?”

Natsuki: (sighs) “It’s definitely tough. Balancing work, taking care of the girls, and making sure they’re happy and healthy…it’s a lot. But seeing them grow and thrive makes it all worth it.”

Monika: “I can imagine. Motherhood isn’t easy, but you’re doing an amazing job.”

Natsuki: (grateful) “Thank you, Monika. I appreciate your support. And congratulations again on your growing family. It’s going to be even more chaotic and wonderful for you with two little ones.”

Monika: (laughs) “I’m excited for the chaos. And don’t hesitate to reach out if you ever need any help or even just someone to talk to, okay?”

Natsuki: (smiling) “I won’t hesitate, thanks Monika. We’ve got each other’s backs, right?”

Monika: (nodding) “Absolutely. We’re a club of friends, after all.”

(As Natsuki watches the children playing happily together, she feels a sense of warmth and support, knowing she’s not alone in this journey of motherhood. Just then, Sayori bursts into the room - her 7 month bump is contracting rapidly.)

Hana, Yumi, Sakura, and Ryū: “Aunt Sayori?!”

Natsuki: (concerned) “Sayori, are you alright? What’s happening?”

Sayori: (breathing heavily) “I think… I’m going into labor, Natsuki. And they’re coming out fast!”

(Sayori quickly gets into a birthing position, but something was wrong - the delivery was causing Sayori so much pain.)

Sayori: (breathing heavily) “But…I don’t think one of the babies is in the right position!”

(Natsuki checks Sayori’s cervix, and finds out why Sayori was in so much pain.)

Natsuki: (worried) “Sayori, you’re right. The first baby is breech. I’ll try to get it into the correct position. Once I’m finished, push as hard as you can! Let’s bring these twins into the world!”
Supported nvidia driver for GTX 960