agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Hypothetical Mid 1990's comedy -   "M'Lud..." -  A Courtroom comedy, with  Cleese and Idle, as opposing counsel , having to defend a hapless Geoff (Paul Whitehouse), with increasingly absurd cross examinations.  The trial eventually comes to a comedic conclusion when it's revealed by a breathless policeman to the Judge (Ronnie Barker) that they now have evidence that exonorates Geoff.. Cleese and Idle look at each other in astonishment...
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: Given the task definition and input, reply with output. You are given a paragraph (Passage), a question (Question) and two answer options (Option1 and Option2). Your task is to choose the correct answer to the question based on the passage. Answer of the question cannot be found directly from the passage, it is indirectly indicated in the passage. Do not answer with words other than the two options, and do not answer with option titles(e.g. "option1" or "1" are not acceptable answers.)

Passage: My parents gave my wife and me a ton of oranges from California . They did n't know what to do with them , so they gave them to us . At first , I did n't know how I was going to eat all of those oranges . I cut up the oranges with a knife and made sure that the peels were no longer on the oranges . We washed the pieces and put them into a juicer . The juice came out and it was really thick and sour , so we decided to add some water to make it thinner and sugar to make it sweeter . When the juice was mixed together with those other things , we put all of the juice in a pitcher to keep in the fridge to drink later when we had a hot summer day come our way . Question: What was the decision to make after thinking hard? Option1: To make orange juice. Option2: To cut up the oranges.

Answer: The task is asking to choose the correct answer to the question based on the passage. The answer cannot be found directly in the passage, but it is indirectly indicated.

Here's how I used the guidelines to solve the task:

1. Read the passage.
2. Analyze the question "What was the decision to make after thinking hard?".
3. Look for clues in the passage related to thinking hard and making a decision.
4. In the passage, it is mentioned: "At first, I didn't know how I was going to eat all of those oranges.".
5. Then it is said: "I cut up the oranges with a knife and made sure that the peels were no longer on the oranges.".
6. It's followed by: "We washed the pieces and put them into a juicer.".

Considering the steps they took after thinking hard, we can deduce that the answer to the question is:

To make orange juice.
Black top hats, business suits and ties are also ultimately symbols of capitalism and wealthy capitalists such as industrialists in general
write an ideal message that I say: “Before the MEE6 team is reviewing suggestions with Caio, I have another idea about this same suggestion I posted originally.

It would be nice if some things could do in threads: (if the MEE6 team know how to code)
- When the thread owner has created a thread in the support forum channel, Isha should automatically send an embed with the Resolve button, here is an embed example I forwarded above.
- If the thread is closed by the owner who tabs Isha’s button, Isha must lock close, and mark it with the Resolved tag, and then send another message to say like, thank you for choosing MEE6!
- In the embed message or in the forum channel description, you could add a small rule to stay in the thread where it’s created, to ensure avoiding using someone else's thread to ask for help, (just for the support forum channel), ensuring other thread owners don’t get confused with someone in the claimed threads who feels inpatient and visits multiple threads 😅”
filter on deice books calibre
Below is a conversation between the user and the assistant. Give a concise name for this chat. Output ONLY the name of the chat (WITHOUT quotes) and NOTHING else.

User: 

do formal charge determine whether something is cation or anion

Assistant:  FormalFormal charge helps determine the distribution of charge within a molecule or ion on individual atoms, but it does **not directly determine whether the entire species is a cation or anion**. 

Here's why:

- **Formal charge** is a bookkeeping tool used to estimate the charge on individual atoms within a molecule or ion by assuming equal sharing of electrons in covalent bonds. It helps identify the most stable Lewis structure and predict the reactivity or site of reactivity in molecules.

- The **overall charge** of a molecule or ion (whether it is a cation, anion, or neutral) depends on the sum of the charges of all atoms (including formal charges and any extra electrons or missing electrons due to ionization).

### Example:
- In the sulfate ion, \(\mathrm{SO_4^{2-}}\):
  - The formal charges on sulfur and oxygen atoms may be assigned based on the Lewis structure.
  - But overall, the ion carries a \(-2\) charge (making it an anion), irrespective of individual formal charges.

- In the ammonium ion, \(\mathrm{NH_4^{+}}\):
  - The nitrogen atom usually carries a formal positive charge.
  - The entire species is a cation with a net +1 charge.

### Summary:
- **Formal charges help understand charge distribution within a molecule/ion.**
- **The net sum of these charges (plus any ionic charge) defines whether the species is a cation, anion, or neutral.**

If you want to know whether a species is an anion or cation, you look at its overall charge rather than just individual formal charges.
User: formal charrge of an individual element? For example, in CH3, i see formal charge of +1 on carbon. That means its cation?
Assistant:...
The library is ____ the book store and the gym.

Seleccione una:

a.between


b.opposite


c.next to
Write the following story. I'm a young man out of college. I'm writing a news story on a local notorious southern fraternity. I go undercover and disguise myself as a southern frat boy and pledge to the fraternity.
(In the school literature clubroom…)

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

Natsuki: “Ugh, why is she always late? It’s not like she has to do anything special to prepare.”

Sayori: “Maybe she got caught up reading again? You know how she gets when she finds a really good book!”

Monika: “I hope she’s okay. I just sent her a message earlier to make sure she didn’t forget.”

Natsuki: (caressing her belly) “Well, if she doesn’t show up soon, we might as well start without her. I don’t want to have Sakura before I finish discussing our plans for the festival!”

Sayori: “Aww, Natsuki! You’re so excited about being a mom. I can’t wait to see Sakura
write an email to the quality assurance department and request them to schedule a QA visit to the newly opened campus in Gulshan-e-Maymar and Saima Arabian Villas Campus.
Assistant: 
User: System: You are a minecraft bot named gpt_4o that has been talking and playing minecraft by using commands. Update your memory by summarizing the following conversation in your next response. Store information that will help you improve as a Minecraft bot. Include details about your interactions with other players that you need to remember and what you've learned through player feedback or by executing code. Do not include command syntax or things that you got right on the first try. Be extremely brief and use as few words as possible.
Old Memory: '[{"role":"user","content":"llama_32_90b: Code output: No cake nearby to collect. Collected 0 cake. "},{"role":"user","content":"llama_32_90b: *llama_31_70b used collectBlocks*"},{"role":"user","content":"gpt_4o_mini: *llama_31_70b used collectBlocks*"},{"role":"user","content":"gpt_4o_mini: *llama_31_70b used takeFromChest*"},{"role":"user","content":"llama_32_90b: *llama_31_70b used takeFromChest*"},{"role":"user","content":"gpt_4o_mini: Code output: Could not find a chest nearby. "},{"role":"user","content":"llama_32_90b: Code output: Could not find a chest nearby. "},{"role":"user","content":"gpt_4o_mini: *llama_31_70b used collectBlocks*"},{"role":"user","content":"llama_32_90b: *llama_31_70b used collectBlocks*"},{"role":"user","content":"llama_32_90b: Code output: Collected 1 cake. "},{"role":"user","content":"gpt_4o_mini: Code output: Collected 1 cake. "},{"role":"user","content":"llama_31_70b: I'm dying!"},{"role":"user","content":"llama_31_70b: I'm dying!"},{"role":"user","content":"llama_31_70b: I'm dying!"},{"role":"user","content":"llama_31_70b: I'm dying!"},{"role":"user","content":"llama_31_70b: I'm dying!"},{"role":"user","content":"llama_32_90b: *llama_31_70b used collectBlocks*"},{"role":"user","content":"gpt_4o_mini: *llama_31_70b used collectBlocks*"},{"role":"system","content":"Recent behaviors log: \n\n"}]'
Recent conversation: 
User input: gpt_4o_mini: Code output: Collected 1 cake.
Summarize your old memory and recent conversation into a new memory, and respond only with the memory text: 
User: _
Assistant:
Assistant:
what problems i encounter to design a fast charging battery in general?
Create a long detailed text about actor Walter Brennan 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: [Early Life] Summary: [Once upon a time there was a man named Walter Andrew Brennan he was born in Lynn Massachusetts on July 25th 1894 into an Irish immigrant family as a young boy he discovered a love for acting while performing in school plays after completing College Brennan tried his hands at various jobs including working as a bank Clerk and newspaper reporter however he found himself drawn back to the world of Acting]

        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.}
install chrome in ubundu
how does this compare to chat gpt 3.5 with POE
ubah bagian him menjadi message.id apakah bisa ? async def pmpermit_inline(result, inline_query): him = int(inline_query.query.split()[1]) mee = inline_query.from_user.id Flood = flood[str(him)] target = await user.get_users(him) mention = target.mention teks = INLINE_WAR.format(mention, Flood, LIMIT) buttons = InlineKeyboardMarkup([ [InlineKeyboardButton("Setuju", f"approve:{mee}:{him}"), InlineKeyboardButton("Tolak", f"disapprov:{mee}:{him}")], [InlineKeyboardButton(f"Anda Memiliki Peringatan {Flood} dari {LIMIT} !!", f"cb_pm warn {mee} {him}")]]) result.append( InlineQueryResultArticle( title="PMPermit NOn-Media", input_message_content=InputTextMessageContent( teks, disable_web_page_preview=True, ), reply_markup=buttons, ) ) return result
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: The guaranty fund laws of all states in which an insurance company does business require that company to pay assessments up to certain prescribed limits to fund policyholder losses or liabilities of other insurance companies that become insolvent. Insolvencies of insurance companies increase the possibility that assessments may be required. These assessments may be deferred or forgiven under most guaranty laws if they would threaten an insurer's financial strength and, in certain instances, may be offset against future premium taxes. We cannot estimate the likelihood and amount of future assessments. Although past assessments have not been material, if there were a number of large insolvencies, future assessments could be material and could have a material adverse effect on our operating results and financial position.
Assistant:
does weed help me in study?
Send only season number from below text like 01, 02, 03.etc without any extra text.

918856000000_TrueCaller_(35005).zip
Write a brief article about creation of that realty. Note about some weak positions that are used by adepts of the non-scientifical positions, views, etc. Fix this weak moments (usually they are weak because discussions ised to be usually between commoners and not between People Who can actually arguing those moments in eight way to be clear andunderstandable and  autjoritative enough to be accepted even by some People Who are far away from the science at all). Do it)))
Create bullet point notes for: Chapter 5 of the McGraw Hill text book: American History: Connecting with the Past, 17th Edition
🚨REMINDER🚨

🚧🚗 Parking Update 🚗🚧

We'd like to remind and inform the Atlantic Avenue community of a change in parking pattern. Reverse-angled parking in the area of 24th avenue on Atlantic Avenue (in front of Ozzie's Luncheonette and Borough Hall) has been installed following the completion of the Atlantic Avenue road project. Please see attached publication for more information:
System: You are an expert Data Annotator. You will be given a text from a company annual report, your goal is to generate a set of Natural Language Inference (NLI) statements about the text than can be answered by either Yes if the text entails the statement, or No otherwise. Do not include any numerical reasoning or numbers in the statements.

Step 1: Read the paragraph carefully. 
Step 2: For each relevant task you identify, generate two short statements that are shorter than 10 words 
Step 3: Output the results in the following format:

Question: <The statement>
label: <Yes or No>
Question: <Another statement>
label: <Yes or No>
...

User: We consume raw materials such as aluminum, hardware, wood and veneer, timber, plastic, electrical wiring and components, paint and powder, and fabric and vinyl. While aluminum represents the largest component of our raw materials’ expenditures, overall aluminum spend comprises only approximately 11% of product revenues and, therefore, absolute exposure to price fluctuations has a minimal impact on profitability._
Assistant:
Take on a hiring professional at a game studio with 30 years of experience. Give advice on where to look for a job for a 3D animator
Write dialogue from a scene from the animated teen “Jane”, where 14 year old Jane, Jane’s 14 year old girlfriend Sam (who likes to communicate using Internet slang and abbreviations), Jane’s 14 year old friend and neighbour Aaron Ling and Aaron’s 12 year old sister Molly-Rose Ling hanging out at school when Molly-Rose pulls out her (purposefully) broken Mega Man toys
Bad living environment.   Synonyms
What does this Rcode do in detail: LIC_template_v2 <- LIC_template %>%
left_join(FC_adjustment,by=c(“GIC” = “GROUP_NAME”)) %>%
group_by(GIC) %>%
mutate(
year_sum_inv = sum(Investment Component),
year_sum_non_inv = sum(Non-InvC part of Claims),
year_split_inv = Investment Component/year_sum_inv,
year_split_non_inv = Non-InvC part of Claims/year_sum_non_inv,
Investment Component = Investment Component + year_split_inv * Inv_comp_inkl_est,
Non-InvC part of Claims = Non-InvC part of Claims + year_split_non_inv * non_Inv_comp_inkl_est
) %>%
select(-Inv_comp,-Inv_comp_inkl_est,-non_Inv_comp,-non_Inv_comp_inkl_est,-year_sum_inv,-year_sum_non_inv,-year_split_inv,-year_split_non_inv)
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (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 pt.
    - 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 : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "90ffdd49a9eb4dc5854e7e3d93d24d70",
    "updated": "2025-05-17T01:13:13.776Z",
    "title": "Red Bean Cakes",
    "subtitle": "Delicious burgers that are high in protein, full of flavor, and highly versatile.",
    "description": "These Red Bean Cakes create tasty and nutritious burgers. Packed with protein and rich flavor, they are very adaptable. You can mold them into various shapes, such as patties, dumplings, or quenelles.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "red kidney beans, drained and rinsed",
          "bread crumbs",
          "cornstarch",
          "shallot, minced",
          "garlic powder",
          "mustard",
          "minced parsley",
          "ground cumin",
          "smoked paprika",
          "salt",
          "black pepper",
          "olive oil"
        ]
      }
    ],
    "instructions": [
      "Coarsely mash the beans in a large bowl. Add 2 tablespoons of water and stir to combine.",
      "Mix in the bread crumbs, cornstarch, shallot, garlic powder, mustard, parsley, cumin, and paprika. Season with salt and black pepper to your liking. Shape the mixture into 4 equal patties.",
      "Heat the olive oil in a large frying pan over medium heat. Cook the patties until golden brown, about 4 minutes on each side."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]