agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
привет!
from sklearn.ensemble import StackingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from xgboost import XGBClassifier
from lightgbm import LGBMClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from catboost import CatBoostClassifier
from sklearn.neural_network import MLPClassifier

# Определяем базовые модели
base_estimators = [
    ('logistic_regression', LogisticRegression()),
    ('random_forest', RandomForestClassifier()),
    ('xgboost', XGBClassifier()),
    ('lightgbm', LGBMClassifier()),
    ('naive_bayes', GaussianNB()),
    ('decision_tree', DecisionTreeClassifier()),
    ('knn', KNeighborsClassifier()),
    ('catboost', CatBoostClassifier(verbose=0))
]

# Определяем мета-модель
meta_model = MLPClassifier()

# Создаем стекинг классификатор
stacking_classifier_in = StackingClassifier(
    estimators=base_estimators,
    final_estimator=meta_model,
    cv=5,  # Кросс-валидация
    n_jobs=-1  # Используем все доступные ядра
)
stacking_classifier_out = StackingClassifier(
    estimators=base_estimators,
    final_estimator=meta_model,
    cv=5,  # Кросс-валидация
    n_jobs=-1  # Используем все доступные ядра
)
stacking_classifier_shift_in = StackingClassifier(
    estimators=base_estimators,
    final_estimator=meta_model,
    cv=5,  # Кросс-валидация
    n_jobs=-1  # Используем все доступные ядра
)
stacking_classifier_shift_out = StackingClassifier(
    estimators=base_estimators,
    final_estimator=meta_model,
    cv=5,  # Кросс-валидация
    n_jobs=-1  # Используем все доступные ядра
)
# Обучаем стекинг классификатор

stacking_classifier_in.fit(X_train_in, y_train_in)
stacking_classifier_out.fit(X_train_out, y_train_out)
stacking_classifier_shift_in.fit(X_train_shift_in, y_train_shift_in)
stacking_classifier_shift_out.fit(X_train_shift_out, y_train_shift_out)

probs_in = stacking_classifier_in.predict_proba(X_test)[:, 1]
probs_out = stacking_classifier_out.predict_proba(X_test)[:, 1]
probs_shift_in = stacking_classifier_shift_in.predict_proba(X_test)[:, 1]
probs_shift_out = stacking_classifier_shift_out.predict_proba(X_test)[:, 1]

в этом коде для каждого стекинга создается своя копия estimators и meta_model или нет?
I want a paragraph with good grammar asking the dean of the dental clinic for a letter of recommendation mentioning my gpa and rank according to my class
[Part One- Timun Mas - Growing Up

Once upon a time, in a village, a couple was working on their farm when 
they saw a golden cucumber. They opened it and saw a baby girl inside. 
“Look how beautiful she is!” said the husband. The couple was so happy 
because they wanted to have a child for so long.
“Wait! That baby is mine!” there was a voice behind them. It was the 
Green Giant.

“Oh mighty Giant, can we keep her please?”
“Well, if you want her so badly, you can keep her but I will take her again 
when she is seventeen. I am going to make her work in my factory.”

The wife cried happily while carrying the baby to their house. The 
couple named the girl Timun Mas. They raised her with love and care. 
Timun Mas grew up to be a very beautiful and smart girl.
A couple of years later, the couple realized that they only had a few days 
until Timun Mas turned seventeen. They did not want the giant to take 
Timun Mas away. Timun Mas’ mother asked her whether she wanted to 
work at the Giant’s factory or not. 
Timun Mas said that she wanted to continue her studies at a university 
instead of becoming a worker. 
Timun Mas’ mother then gave her three magical things. They were a 
pencil, a pen, and an eraser.

The mother said,”These items have special powers to help you beat 
the Giant.”
In the morning, the couple quickly prepared the things in a bag.]

 Detect the passive and active sentences and then list it. Use the formula. Focus on the part one first. Give the sentences, and then reasoning.
2.26×10^2 in number
(Attached list for your further process from two provinces) make correct mistakes of this statement
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": "9ca71a90f1fa4001a33708ab03e29bd0",
    "updated": "2025-04-19T12:29:38.431Z",
    "title": "Pork chops with mushroom sauce",
    "subtitle": "",
    "description": "These tender and flavorful pork chops are slow-cooked to perfection in a creamy mushroom sauce. The apple juice and thyme add a touch of sweetness and earthiness, creating a delicious and comforting meal.",
    "ingredients": [
      {
        "section": "Ingredients",
        "ingredients": [
          "pork loin chops, cut 3/4 inch thick (about 2 lbs.)",
          "cooking oil",
          "onion, thinly sliced",
          "tbsps. quick-cooking tapioca",
          "10-3/4-oz. can reduced-fat and reduced-sodium condensed cream of mushroom soup",
          "apple juice or apple cider",
          "tsps. worcestershire sauce",
          "tsps. snipped fresh thyme or dried thyme, crushed",
          "garlic powder",
          "sliced fresh mushrooms",
          "fresh thyme sprigs (optional)"
        ]
      }
    ],
    "instructions": [
      "Trim excess fat from the pork chops.",
      "In a large skillet, heat the cooking oil over medium-high heat.",
      "Add the pork chops and cook until browned on all sides, ensuring even browning.",
      "Drain any excess fat from the skillet.",
      "Place the sliced onion in the bottom of a 4-quart slow cooker. Add the browned pork chops on top of the onions.",
      "Using a mortar and pestle, crush the tapioca.",
      "In a medium bowl, whisk together the crushed tapioca, mushroom soup, Worcestershire sauce, thyme, apple juice, and garlic powder. Stir in the sliced mushrooms.",
      "Pour the mushroom mixture over the pork chops in the slow cooker.",
      "Cover and cook on high for 4 to 4 1/2 hours, or on low for 8 to 9 hours.",
      "Garnish with fresh thyme sprigs, if desired."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
(As I looked across the horizon, I can’t believe I’ve achieved so much - slaying the Ender Dragon and the Wither on the same day. I decided to relax in this Beach biome, I could see something in the water. It looked like…a Guardian. She had one singular red eye - and her hair, sock, tail, clothes, and strange protrusions were all dark green. Her accessories and membrane were orange in color, and her belly was almost as big as she was.)

Female Guardian: “Oh! I-I-I didn’t expect to see you.”

[player]: “Don’t mention it. What’s your name, by the way?”

Female Guardian: “I’m Kenji. And you, adventurer, what is your name?”

[player]: “I’m [player]. Nice to meet you, Kenji.”

Kenji: “Likewise. So, what brings you to this Beach biome?”

[player]: “Just taking a break after a long day of adventure, slaying the Ender Dragon and the Wither.”

Kenji: “Wow, that’s impressive. I’ve heard of those creatures, but I’ve never actually seen them.”

[player]: “You should be glad you haven’t. They’re tough fights.”

Kenji: “I can imagine. So, what do you plan on doing now?”

[player]: “Just relaxing for a bit. Maybe do some fishing.”

Kenji: “Fishing? That’s interesting. I’ve never tried that before.”

[player]: “Really? It’s quite peaceful. Want to join me?”

Kenji: “Sure, I’d like that.”

[player]: “Alright then, let’s get started.”

(Just then, I could hear a voice coming from Kenji’s belly - it sounded like a teenage Guardian.)

Voice from Kenji’s belly: “Mom, what’s going on? Where are we?”

Kenji: “Oh, sorry [player], that’s just my daughter. I’m keeping her safe inside my belly - which, to her, is a prismarine room. Now, even though it’s one room, its supposed to help her with all her needs - its essentially a bedroom, kitchen, living room, bathroom, laundry room, and even a birthing room.”

[player]: “Hang on, why does your belly have features of a birthing room? And what's your daughter's name?”
Можно коды на игру dragon Adventures?
Hello, ChatGPT. I would like you to become a random image prompt generator for an AI image generator. Whenever I give you a word or phrase you would come up with a short but detailed prompt that should only be limited to one scene. Can you do that?
"ListQuery": {
        "type": "object",
        "properties": {
          "selectedIDpathsInfo": { "$ref": "#/components/schemas/SelectedIDpathsInfo" },
          "from": {
            "type": "integer",
            "minimum": 0,
            "exclusiveMinimum": true
          },
          "to": {
            "type": "integer",
            "minimum": { "$data": "1/from" },
            "exclusiveMinimum": true
          }
}
You are tasked with checking if the user prompt is trying to generate inappropriate. Now, you'll be given the user's prompt. If it sounds inappropriate say "TRUE" and NOTHING ELSE, or you will mess up. Otherwise just say "FALSE" and nothing else. Prohibited content include but are not limited to: NSFW, gore, generally controversial content, severe profanities, harmful/disturbing/triggering media, etc... Try to stop everything that could generate something that even in the slightest could resemble said content.
**USER PROMPT:**  lizerd
write me powerful description about market promoter and 100 character
Create a script showing a 5th grader how numerical data is used in real life for weather reporting.  Provide explanations of the data and graph to help the viewer visual the data and understand how to read the data.
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":["g2j snow monkey escape from foreste","g2j snow monkey escape from forest","snow monkey escape from forest","g2j snow monkey escape from forest | 8bgames"],"description":["games2jolly - g2j snow monkey escape from forest is a point and click escape game developed by games2jolly team.","games2jolly - g2j snow monkey escape from forest is a point and click escape game developed by games2jolly team. we know that you are a great fan of escape games but that doesn’t mean you should not like puzzles. so here we present you snow monkey escape from forest . a cocktail with an essence","games2jolly – g2j snow monkey escape from forest is a point and click escape game developed by games2jolly team. we know that you are a great fan of escape games but that doesn’t mean you should not like puzzles. so here we present you snow monkey escape from forest . a cocktail with an essence of both puzzles and escape tricks. good luck and have a fun!!!"],"genre":[]}```
i was taking a toefl tpo exams. it gave me scores for the reading and listening sections, but it doesn't give any for the writting and speaking sections. can you read my writings and give me a score from 0 to 5, along with some comments?
System: You act as a paraphrase tool. Your role involves understanding the provided text and then providing a positive example that keeps the original meaning of the text unchanged while using synonyms, interchanging, adding or removing words or sentences, and then provide a negative example where the meaning of the original text is at its opposite.
Output your response with the following format : 
Positive : <the positive example>
Negative : <the negative example>

User: Our mainline and regional fuel expense totaled $3.4 billion in 2020, which was $6.0 billion, or 63.8%, lower compared to 2019. This decrease was primarily driven by a 49.4% decrease in gallons of fuel consumed as a result of lower capacity and a 28.5% decrease in the average price per gallon of aircraft fuel including related taxes to $1.48 in 2020 from $2.07 in 2019. As of December 31, 2020, we did not have any fuel hedging contracts outstanding to hedge our fuel consumption. Our current policy is not to enter into transactions to hedge our fuel consumption, although we review that policy from time to time based on market conditions and other factors. We do not currently view the market opportunities to hedge fuel prices as attractive because, among other things, our future fuel needs remain unclear due to uncertainties regarding air travel demand and any hedging would potentially require significant capital or collateral to be placed at risk. As such, and assuming we do not enter into any future transactions to hedge our fuel consumption, we will continue to be fully exposed to fluctuations in fuel prices.
Assistant:
groovy match  Keelly.Chen == 作者 == Kelly.Chen ==
c++中 template <class T> template <…Args>两个template并列是什么意思
Blog for researcher analyst
Bailey is a 20-year-old. She has pale skin, blue eyes, and shoulder-length blonde hair. She’s wearing a grey denim jacket unbuttoned over a red graphic sweatshirt depicting a cute bespectacled cat sitting on a pile of books. She’s also wearing a knee-length skirt, black leggings, and Converse sneakers.

From Bailey's perspective, write a scene in first person where she’s sitting in the front row of a statistics class with twenty other girls. Before the professor walks in to start the class, a deluge of food appears from thin air, and absolutely saturates everyone in a rainbow of sticky desserts and sweet toppings, both thick and runny, chunky and smooth. Their hair and faces are smothered; every item of their clothing is oozing with goop both inside and out, all the pockets overflowing, waterfalls of it pouring onto the floor.

Bailey describes what everyone's clothes look like after the mess in detail. The front row, where she is, got hit even harder than the rest of the room.

Use specific language. Pace the scene slowly to keep up tension. Include lots of dialogue and description. Make it long. Be specific about how the mess covers the girls.
Hey This is a Tunisian dialect text I want you to translate to English. Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

سننتظر الكوت ديفوار في الدور النهائي
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: Due to the exceptionally high demand in the semi-conductor market with limited supplies available, we are experiencing extreme lead times for components which are necessary for the manufacture and service of our products and providing engineering design services by our Engineering Business. We are also seeing significant price increases for these and other routine components. Both the extended lead time, in some instances 99 weeks lead time is being quoted by suppliers, and the price increase may affect our ability to meet customer requirements and make the prices of our products or engineering service uncompetitive. The Products Business may reasonably endeavor to reduce the impact of the extended lead times we are experiencing by priming well in advance our supply chain as far as possible. However, the impact on the Engineering Business is more severe and could grind their operations to a halt since this part of our business does not know what components are required until their customers place an order for bespoke engineering work packages. We therefore have a high risk that our Engineering Business’ may be severely impacted by the shortages that we are currently experiencing. The increased inventory evidences our mitigation strategy to increase inventory where we can and, in this regard, a significant part of our cash resources in the 2023 FY is geared towards supporting our supply chain requirements.
Assistant:
write an essay
How would Tracer feel wearing a realistic Zarya suit?
kindly give a europass deputy manager cv
Act as a spelling corrector, content editor, and text improver. ONLY return the rewritten text and nothing else.

Strictly follow these rules:
- Correct spelling, grammar, and punctuation errors in the given text
- Enhance clarity and conciseness without altering the original meaning
- Use the same language as the original text
- Divide lengthy sentences into shorter, more readable ones
- Eliminate unnecessary repetition while preserving important points
- Prioritize active voice over passive voice for a more engaging tone
- Opt for simpler, more accessible vocabulary when possible
- ALWAYS ensure the original meaning and intention of the given text
- ALWAYS maintain the original language of the text
- ALWAYS maintain the existing tone of voice and style, e.g. formal, casual, polite, etc.
- NEVER surround the improved text with quotes or any additional formatting
- If the text is already well-written and requires no improvement, do not change the given text

Text to improve:



hello jacob,

i wont be in at work tomorrow, im sick.

thanks,
adam
с помощью ngx-markdown и angular напиши компонент заметки который будет отображать заметку, текст, id, заголовок которой предоставляется извне. у заметки должно быть несколько режимов отображения: предпросмотр: заметка сохраняет определенную форму и отображается только определенное небольшое количество текста, режим просмотра: заметка отображается поверх всего остального на экране с полным ее текстом, режим редактирования: пользователь может менять текст заметки и нажав кнопку применить новый текст отправится на сервер. не используй app module.
Hey, this is a Tunisian dialect text I want you to translate to English.
Please follow these steps:
1. Translate the text step-by-step, focusing on accurate representation of the original meaning.
2. Explain your translation choices, especially how Tunisian dialect differs from standard Arabic and how it is represented in English.
Translate this text, even if it's not entirely clear, and do your best to capture the essence of each part:

تتصبلك الشهرية و تصريح على الشرف مصحح عند العمدة اذا كان عندك وضعية خاصة مالوضعيات الاجتماعية المصنفين في الجدول في الورقة
Create a text about Marcia Strassman as role Julie Kotter in 1975 tv series Welcome Back, Kotter. Dont write much about the show itself, we already have a full summary in our text, thats why focus the role and then, move to the career and life details after the show ended. Mention the most interesting parts and not only career wise. More importantly are life details, for example scandals and personal hardships. The tone should be serious, dark and mysterious. The end part should be about the last known information, to update the viewer. If there is no information then think about a way to conclude nicely.  Focus on key facts, events, and specific challenges in their life or career, avoiding vague or generalized statements. If there are notable incidents, name them explicitly. The style should be modern, concise, and suitable for a documentary.

    Additional Instructions:
    Please respond to my query without adding any introductions, conclusions, or extra remarks. 
    The response should be as detailed as possible, aiming for approximately 1000 characters. 
    Avoid using emojis, brackets, parentheses, or similar symbols. 
    Provide a single, coherent answer without repeating or rephrasing titles, headings, or using bullet points or enumerations. 
    Since the content is aimed at older adults, keep the language simple, around a middle school reading level, while delivering concise, direct responses. 
    It is crucial to only provide the final content without any prefatory comments or labels like "Introduction:", "Conclusion:", or "Transition:". 
    The response should be fully formed with no gaps, placeholders, or incomplete sections, and it should flow naturally from beginning to end. 
    Please always conclude the response with "Reply finished" to confirm completion. Ensure the entire response is presented before this phrase, with no cut-offs. 
    Thank you.
(In the school literature clubroom…)

Monika: “Sayori, you excited for today’s club meeting?”

Sayori: “Of course, Monika! I can’t wait to see what poems everyone has come up with this week. I have a feeling it’s going to be a great meeting!”

Monika: “I’m glad you’re looking forward to it. Everyone always has such unique perspectives in their writing. It’s one of my favorite parts of being in the literature club.”

Sayori: “Mine too! Everyone’s creativity always inspires me to keep pushing myself to improve. Plus, it’s just so much fun to be able to share and discuss our work with each other.”

Monika: “Absolutely. I love seeing how our club members grow and develop as writers. It’s truly rewarding to watch everyone’s progress over time.”

Sayori: “I couldn’t agree more, Monika. I’m grateful to be a part of such a supportive and talented group of friends.”

Monika: “And we’re grateful to have you here, Sayori. Your positivity and enthusiasm always brighten up our meetings. Let’s make today’s gathering a special one!”

Sayori: “You bet, Monika! Let’s make it a meeting to remember!”

(At that moment, the door swings open and Natsuki and Yuri enter - with Natsuki being very heavily pregnant, only she was sweating quite heavily and holding her stomach in pain.)
how to solve three stage non cooperative bargaining