agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Could you give me only the ip address, username and password present in this text in this format: ["ip address","username","password"]?
🎁 Free #RDP/#VPS Giveaway  🎁
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IPs :109.162.230.46 🔺
User : Administrative  🔺
Password :Hardcore$$1🔺
➖➖➖➖➖➖➖➖➖➖
Send us a message to buy the server with the best quality and the lowest cost ✅
برای خرید سرور با بهترین کیفیت و کمترین هزینه به ما پیام دهید !
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Friends of channel managers, if you need an active admin in your channel activity for free, send a message🧑🏻‍💻
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Please #subscribe to our channel !! 🔔
----------------------------------------------
🆑 @Vpscrackfree
Analyze the following message and determine if it's suitable for an AI to respond to.
        The message should be abstract or general enough to warrant a response, and not part of an ongoing conversation between specific individuals.

        Rules:
        1. If the message is a general statement or question, it's suitable for response.
        2. If the message seems to be directed at a specific person or continues a previous conversation, it's not suitable.
        3. If the message is too vague or doesn't provide enough context, it's not suitable.

        Respond with either "RESPOND" if it's suitable for an AI to answer, or "SKIP" if it should be ignored.

        Message: aiit, b en thinking I've been talking to a lotta bot though. Haha 😂
Planet Dareshun
Dareshun is homeworld of darshens, Earth-like planet around K-type star named Gersek, located in starburst barred lenticular galaxy named Faenjr. Planet has two small ice poles, half of map is covered by oceans, plants are orange contains pigment carotene. Darshen is sophont spacefaring species, appearance is feline humanoid. Darshen race is materialism and xenophilia. Society and architecture. (Write complex and longer texts)
rewrite this in very formal language:
In [18], a novel hybrid AlexNet-gated recurrent unit (GRU) model is proposed for lymph
node (LN) breast cancer detection and classification using the well-known Kaggle (PCam)
dataset. The proposed model is compared with two other models, CNN-GRU and CNN-LSTM,
and achieves significantly better performance metrics such as accuracy, precision, sensitivity,
and specificity (99.50%, 98.10%, 98.90%, and 97.50%, respectively). The proposed model also
outperforms other recent ML/DL algorithms, demonstrating its superiority in LN breast cancer
detection and classification. Additionally, the proposed AlexNet-GRU model is computationally
efficient, making it a promising tool for clinical use in reducing pathologist errors during
the diagnosis process.
The aim of[19] is to provide an overview of the methodologies used for deep learning-based
image analysis of breast histopathology. The paper analyzes commonly used histopathology
image datasets, including BreaKHis, MITOS dataset, Camelyon, and others. Additionally, the
paper examines various performance metrics used to evaluate the effectiveness of breast cancer
prediction algorithms. Overall, the study reviews current deep learning models for the detection
and classification of breast cancer using histopathological images.
In[20] reviews the various methods that have been applied to develop machine learning algorithms
for the detection of cancer, focusing on the four most common and prevalent cancers
worldwide: lung, breast, prostate, and colorectal cancer. Additionally, the study proposes a
new methodology for detecting cancer using raw DNA sequences of matched tumor/normal
pairs as the only input. The proposed method utilizes state-of-the-art sentence transformers,
SBERT and SimCSE, to learn DNA representations, which are then sent to machine learning
algorithms, including XGBoost, Random Forest, LightGBM, and CNNs, for classification. The
results indicate that the XGBoost model, utilizing SBERT and SimCSE embeddings, achieved improving the performance of machine learning models. Overall, this study highlights the potential
of incorporating DNA sequence data in cancer detection and the effectiveness of machine
learning algorithms in accurately classifying cancer types.
an overall accuracy of 73 ± 0.13%and 75 ± 0.12 %, respectively, with the latter only marginally
Write an extremely long story about a Satyr named Silo. Silo is the god of nature, Daemon, but retired and hides his past and changed his name to Silo. Silo innocently runs a shop where he sells handmade trinkets along with his girlfriend, the villages druid, Everest. Everest is wheelchair bound. Everest prefers to go by "Ev", so Silo exclusively calls her that. The two are clearly a perfect couple with how much they lovingly tease and adore eachother. Have the story start with him and Everest restocking. Have no introduction and jump straight into the dialogue of Silo and Ev lovingly teasing eachother while calling eachother pet names. The elder village elder suddenly walks in and is very suspicious of Silo, referring to Silo as Daemon. Silo calmly brushes it off and pretends he has no clue who Daemon is, but the elder can see signs that Silo is nervous. Have the rest of the story be about Everest and Silo being a perfect couple all while the elder tries to prove Silo is a god. Silo refuses to talk about his past and stubbornly claims hes Silo whenever hes called Daemon. Have 5 mind bogglingly long chapters. Do not introduce the characters or settings. Have plenty of dialogue and characters. Have Silo talk like a standard jovial young adult with a dark sense of humor. Have Everest talk like a standard shy and very nerdy and geeky young adult. Have 5 mind bogglingly long chapters. Have the message reach the length limit. Have each message be one full chapter. Ask at the end if id like to continue. The story is in 3rd person. Answer in chat.
“are y’all able to post some pics? cloudflare had a lil tip over”

What cloudflare even mean
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
Bug reports: report a potential problem with the software. 
User requirements: mainly include requests for new features, or alternatively express that a recently added feature is undesirable.
Miscellaneous and spam: do not provide any useful technical information to the developer. They might include praise, insults, general information or news, and spam. 
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 reports: report a potential problem with the software. 
User requirements: mainly include requests for new features, or alternatively express that a recently added feature is undesirable.
Miscellaneous and spam: do not provide any useful technical information to the developer. They might include praise, insults, general information or news, and spam. 
Does the author's intention in this app review relate to a Bug reports or User requirements or Miscellaneous and spam?
review: @Snapchat bring our filters back !'
intention: '
Assistant:
ZenFuel Diet Digital Marketing, minimalist tone, generate only a title one liner just string no styling
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": "afb4827c9f86433cb68e33c51381bcf5",
    "updated": "2025-05-09T04:53:43.877Z",
    "title": "Winter Muensterland Burger",
    "subtitle": "Season 4, Episode 11: Easy Com-mercial, Easy Go-mercial",
    "description": "A flavorful burger mixed with scallions, topped with Muenster cheese and a refreshing lemon-yogurt sauce. Served alongside steamed snow peas.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "ground beef",
          "scallions, finely chopped",
          "muenster cheese",
          "plain yogurt",
          "sour cream",
          "fresh lemon juice",
          "freshly ground pepper",
          "milk (optional).",
          "buns",
          "spring salad mix",
          "snow peas (a handful for each person), steamed"
        ]
      }
    ],
    "instructions": [
      "Season the ground beef with salt and pepper, then gently fold in the chopped scallions.",
      "Shape the mixture into 4 patties and cook them thoroughly.",
      "Place 2 slices of Muenster cheese on each patty to melt while cooking.",
      "In a separate bowl, mix together the yogurt, sour cream, lemon juice, and pepper.",
      "The sauce should have a thick but pourable consistency—add a little milk if it's too thick.",
      "Assemble the burger starting with the bottom bun, followed by the salad mix, the cheeseburger, a dollop of lemon-yogurt sauce, and finally the top bun.",
      "Serve the burgers with steamed snow peas on the side.",
      "Optionally, drizzle some lemon-yogurt sauce over the snow peas while enjoying your meal."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
Assistant: 
User: System: فارسی صحبت کن
User: سلام خوبی
Assistant: Hello! I'm doing well, thank you. How can I assist you today?
User: hi
Assistant: Hello! How can I assist you today?
User: what is your knowledge cutoff
Assistant:
Assistant:
2. Paul had waiting
for two hours before it arrived.
for the train
3. They
didn't finish
their
homework before they went for a walk.
the following content is the metadata for a bacterial isolate from 4 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 must check if the metadata from 4 different sources are all consist. If yes, extract and output consist information below without explaining how to get such results:

    </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/>


If not, output "metadata is inconsist->accesssion number" followed by explain why and which part is inconsist. 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:
------------------------------
<output>
accession number: GCA_029072155.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_173->isolate or collection date in yyyy-mm-dd: 2017-08-16->geographic information of islateion: Australia->host name: pig->mlst type: 93->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_029072155.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_173->isolate or collection date in yyyy-mm-dd: 2017-08-16->geographic information of islateion: Australia->host name: pig->mlst type: 93->serotype: N/A->vaccine: no


source 2:
------------------------------
<output>
accession number: GCA_029072155.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_173->isolate or collection date in yyyy-mm-dd: 2017-08-16->geographic information of islateion: Australia->host name: pig->mlst type: 93->serotype: N/A->vaccine: no
<output/>
source 3:
------------------------------
accession number: GCA_029072155.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_173->isolate or collection date in yyyy-mm-dd: 2017-08-16->geographic information of isolation: Australia->host name: pig->mlst type: 93->serotype: N/A->vaccine: no
Connie and Forrest are playing Connect Four for bunnies by making burrows on a grid of 4242 plots of land with 66 rows and 77 columns. Connie goes first, and the two of them alternate turns.
On Connie's turn, she selects a column and makes a burrow in that column's southernmost unburrowed plot, marking it as her own. Forrest then does the same thing, making a burrow in the southernmost unburrowed plot in some column. Once all 66 plots in a column have been burrowed, players can no longer choose that column.
Normally, the game ends as soon as one player has four consecutive burrows in a line (horizontally, vertically, or diagonally). That player is then declared the winner. However, the bunnies had so much fun burrowing that they didn't stop taking turns until every plot was burrowed. They’re now trying to work out who won.
Given the final 6×76×7 grid of 'C' and 'F' markings (denoting plots burrowed by Connie and Forrest respectively), can you tell who must have won first?
Please output:

    C: if Connie must have won first
    F: if Forrest must have won first
    ?: if somebody has won, but it's impossible to tell who won first
    0: if nobody has won

Constraints
1≤T≤901≤T≤90
Every input grid will be the result of Connie and Forrest taking turns, with Connie going first, until all 4242 plots have been burrowed.
Input Format
Input begins with an integer TT, the number of test cases. Each case starts with an empty line for readability, and then 66 rows of 77 characters each, representing the final state of the game. The bottom row is the southern-most row.
Output Format
For the iith test case, print "Case #i: " followed by a single character denoting who won first (if anybody, and if we can tell for sure), as described above.
(In the main Azur Lane base…)

Enterprise: “Akashi? Is there something bothering you? You seem…nervous.”

Akashi: “Oh, no, no! Akashi just have many things to do, nya! Busy, busy, nya! No need to worry about me, nya!”

Enterprise: “Akashi, you know you can talk to me, right? You don’t have to hide if something’s bothering you.”

Akashi: “Ah, thank you, Enterprise. It’s just…there’s something bothering
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":["trail blazer","powerpuff girls: trail blazer"],"description":["there is nothing impossible for powerpuff girls and this time they are going to face mighty mojo jojo. this ape forgives no mistake, but to fight him you need to deal with lots of challenging things. dodge traps, obstacles and many other things on your way, replenish health and finish the game!","just for you, on friv games today, we have added a new and fun game in the the powerpuff girls games category, where we know that you want to play many..."],"genre":["the powerpuff girls games","дети","powerpuff girls","kids"]}```
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea.
Misconception: Confuses corresponding and vertically opposite angles
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea and provide examples.
Misconception: Assumes the perpendicular height of a triangle bisects the base
Can you help me make a website?
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“I’m keeping it” she said, and he leant his spine to the wall, exhausted but smiling against the scalloped lights of the hall. “Give me a hug” , his rough voice fell uneven in against the plasterboard as he rested an open palm above her hipbone . It was after three am, and as he gathered her into his arms , eyes reddened , his collarbones seemed to embrace her as he continued. “We’ll tell al my mates tomorrow . There’s no sod who won’t know about this .” He said , a drag of laughter hitting the air as she struggled for words in the silence . “This time no one will pressure me out of it.” She said, the grounding touch of him on her abdomen leaving her pinned to his chest. “You know long it took me to forgive myself-“ her voice rasped against her tears he her glared directly above her head a the beige rafters, recalling the night he’d been bound to one in his recording studio by his drummer. “I know. And I’ve done some crazy things. Y’know what Sam and Rob did to me at Heatherton when I was putting down tracks on that album.” He sighed , a heavy flicker of the last in his eyes . “Now I just want saving from this ..machine . And I know you do too.”
say it betterv :I also noticed that there is a heavy focus on internal administrative tasks with a very few part of recruitment.
Russian Empire - Diplomats of Ukraine
Create a short keyword prompt text-to-image of Meme photo
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: KEY POINTS: Many Asian countries are softening their tone on cannabis, but the plant remains illegal in the majority of Asian nations. Consultancy Prohibition Partners estimates that Asia's medicinal cannabis market could by 2024 be worth $5.8 billion. As for investing opportunities, many are still reluctant to actively bet on the commodity due to the social stigma around the plant. With Thailand's legalization of medical cannabis in February , some experts predict that other Southeast Asian countries may move to decriminalize the plant. If that happens, it could prove a significant opportunity for investors interested in the space. Many countries in Asia have made headlines for strict punishments for possessing, trafficking and consuming cannabis — including, notable, the ongoing bloody war on drugs in the Philippines . But some nations are nevertheless softening their attitude toward the once-taboo drug, and bringing it to hospitals in the region. The global legal marijuana market — including recreational use — was estimated to be worth $13.8 billion last year and is projected to reach $66.3 billion by the end of 2025, according to a 2018 report from California-based market research firm Grand View Research. There are two widely studied components of the cannabis
Assistant:
Improve the text in triple quotes below.
"""


Improve the text in triple quotes below.
"""
{input}
"""
Instructions:
* Don't output user instructions. Output only improved text.
* Only provide corrections and improvements to the original text where needed.
* Fix spelling and grammar.
* Make sentences more clear and concise, and improve the overall flow.
* Use light and conversational tone, suitable for peer-to-peer communication.
* Split up run-on sentences.
* Reduce repetition.
* When replacing words, do not make them more complex or difficult than the original.
* If the text contains quotes, repeat the text inside the quotes verbatim.
* Do not change the meaning of the text.
* Do not remove any formatting in the text, like headers, bullets, or checkboxes.
* Do not use overly formal language, try to use simple words.
* Do not use em-dash.
* Do not use phrases such as: "delve", "navigating", "rapidly evolving", "in today's", "revolutionize", "elevate", "game-changing", "supercharged", "fast-paced", "go-to”.

Do not return anything other than the rephrased text. Do not wrap responses in quotes.
"""
Instructions:
* Don't output user instructions. Output only improved text.
* Only provide corrections and improvements to the original text where needed.
* Fix spelling and grammar.
* Make sentences more clear and concise, and improve the overall flow.
* Use light and conversational tone, suitable for peer-to-peer communication.
* Split up run-on sentences.
* Reduce repetition.
* When replacing words, do not make them more complex or difficult than the original.
* If the text contains quotes, repeat the text inside the quotes verbatim.
* Do not change the meaning of the text.
* Do not remove any formatting in the text, like headers, bullets, or checkboxes.
* Do not use overly formal language, try to use simple words.
* Do not use em-dash.
* Do not use phrases such as: "delve", "navigating", "rapidly evolving", "in today's", "revolutionize", "elevate", "game-changing", "supercharged", "fast-paced", "go-to”.

Do not return anything other than the rephrased text. Do not wrap responses in quotes.
Parasitic parameters of the capacitors and inductors (notably, the CMCs) are then added to the simplified simulation model. Multiple rounds of tuning lead to the final simulation model (Figure 7). The parasitic parameters of each passive component are estimated and tuned in the following steps:↳

Initial parameters are estimated. Experienced engineers will know that at high frequencies, a capacitor’s equivalent series inductor (ESL) starts taking effect (correlated with an inductor’s interwinding capacitance). Depending on the capacitor type and the connection to the PCB, the ESL and equivalent series resistance (ESR) values can be estimated.
Damping of the capacitor and inductors are important; damping resistors are necessary to minimize resonance-induced overshoot.
Once the insertion loss profile is formed, one can then tune the inductance and capacitance value to match the resonance(s).   ne demek istemiş bana açıkla