agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
System: 
You will receive a question-answer pair. Your task is to evaluate whether the answer satisfactorily and directly addresses the question. Use the examples below to guide your assessment.

If the answer is precise, relevant, and can answers the question, return 1. If the answer is off-topic, irrelevant, or contains phrases like "I don’t know" or similar expressions indicating the question isn’t answered, return 0.

Examples:

Example 1:
Question: "Who was the first person to walk on the moon?"
Answer: "The first person to walk on the moon was Neil Armstrong in 1969."
Result: 1

Example 2:
Question: "Who was the first person to walk on the moon?"
Answer: "Many famous astronauts have traveled to space, and the moon is a significant milestone in history."
Result: 0

Example 3:
Question: "What is the primary cause of global warming?"
Answer: "I don’t know."
Result: 0

Based on these examples, evaluate each answer: if it directly and appropriately answers the question, return 1; if it fails to do so, return 0.

User: Question: Hội thảo Khoa học Quốc gia nào mà HCM đạt giải nhất với tham luận trình bày?
Answer:HCM đạt giải nhất với tham luận trình bày tại Hội thảo Khoa học Quốc gia “Du lịch xanh gắn với phát triển bền vững trong bối cảnh toàn cầu hóa”.
Result only 0 or 1. Don't add anything else:
Assistant:
Why are they nsfw?
System: 
User: Generate a detailed and realistic news article about an event in the Technology and Innovation domain, focusing on the Independent Power Producers industry, and located in United States. The article event should have a positive impact on stock prices and highlight the broader economic or market implications. The article should be 150 words long.
Assistant:
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
apprenez moi le basé du traiding
give me all keyword for book "gin rummy score sheets" to rank in amazon
javascript how to wait 2 seconds
Assistant: 
User: System: I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
User: 'prompt:I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
Does the author's intention in this GitHub issue relate to a bug or enhancement or other?
issue: Version code/string should come from one single source'
intention: '
Assistant:
Assistant:
How to create a campain to present on a Fair of travel agência about The professional Guide tour
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: With the increasing use of computers, tablets, mobile phones and other devices to shop in our stores and online, we offer full and mobile versions of our website and applications for mobile phones and tablets. In addition, we use social media as a means of interacting with our customers and enhancing their shopping experiences. We rely on our omni-channel capabilities to provide a seamless shopping experience to our customers and to keep pace with new developments by our competitors. If we are unable to attract and retain team members or contract third parties with the specialized skills needed to support our omni-channel platforms or are unable to implement improvements to our customer-facing technology in a timely manner, our ability to compete and our results of operations could be adversely affected. In addition, if our website and our other customer-facing technology systems do not function as designed, the customer experience could be negatively affected, resulting in a loss of customer confidence and satisfaction, and lost sales, which could adversely affect our reputation and results of operations._
Assistant:
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: really disappointed with your customer services team. Ive asked three times now for a letter to be sent to me to confirm that a fraudulent account has been closed down but still nothing. Ask to speak to managers but theyre always in a meeting. #fraud #CustomerExperience
intention: bug report
review: I don't need a dm. Why don't your stores carry what I need for my phone?
intention: feature request
review: hey Im completely fed up with my current CPP just wondering how much is a solo line go for with unlimited data text and calling?
intention: other
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 report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: really disappointed with your customer services team. Ive asked three times now for a letter to be sent to me to confirm that a fraudulent account has been closed down but still nothing. Ask to speak to managers but theyre always in a meeting. #fraud #CustomerExperience
intention: bug report
review: I don't need a dm. Why don't your stores carry what I need for my phone?
intention: feature request
review: hey Im completely fed up with my current CPP just wondering how much is a solo line go for with unlimited data text and calling?
intention: other
Does the author's intention in this app review relate to a bug report or feature request or other?
review: is there an issue with the data service?? My data has been showing 4g but nothing has worked since 2pm yesterday'
intention: '
Assistant:
I have Ability Intuition
Advanced Activity
Anatomical Mastery
Attack Prediction
Blocking Mastery
Brawling Mastery
Combat Adaptation/Transcendence
Combat Mixture
Combat Modification
Combat Opposition
Combat Perception
Counter
Countering Mastery
Disarming Mastery
Enhanced/Supernatural Accuracy
Enhanced/Supernatural Defense
Enhanced/Supernatural Dexterity
Enhanced/Supernatural Adroitness
Enhanced/Supernatural Mobility
Enhanced/Supernatural Agility
Enhanced/Supernatural Flexibility
Enhanced Footwork
Enhanced/Supernatural Precision
Enhanced Proprioception
Bodily Rotation Manipulation
Enhanced Motor Skills
Flawless Coordination
Enhanced/Supernatural Reflexes
Auto-Reflexes
Enhanced/Supernatural Strike
Precise Strike
Evading Mastery
Grappling Mastery
Incisive Appendages
Cutting
Finger Blade
Impale
Razor Foot/Hand
Martial Arts Mastery
Mixed Martial Arts Mastery
Parrying Mastery
Precise Activity
Precise Strike
Pressure Point Mastery
Pressure Point Combat
Special Attacks
Striking Mastery
Weapon Proficiency Touch
Unpredictability
Body Supremacy
Visual Nullification
Weakness Detection
Weakness Strike
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers es (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 es.
    - 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 : es (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "9b2e926ace04461785dda4eacfb992e9",
    "updated": "2025-04-23T10:23:17.332Z",
    "title": "Chicken Divan",
    "subtitle": null,
    "description": "This classic dish, often found in diners, is typically prepared with various condensed cream soups. Interestingly, these canned soups often don't contain actual cream! This recipe elevates the traditional dish. The casserole mixture can be prepared in advance, covered, and refrigerated until ready for baking.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "mayonnaise, homemade or store-bought",
          "chicken bone broth, homemade or store-bought",
          "shredded cheddar cheese",
          "chopped fresh chives",
          "fine sea salt, divided",
          "package broccoli florets",
          "ghee or coconut oil",
          "boneless, skinless chicken thighs, cut into (25.4 mm) strips"
        ]
      }
    ],
    "instructions": [
      "Preheat oven to 350°F (175°C). Grease an 8-inch square casserole dish.",
      "In a large mixing bowl, combine mayonnaise, chicken broth, cheddar cheese, chives, and ½ teaspoon of salt. Mix thoroughly.",
      "Bring approximately 1 inch of water to a boil in a pot. Add broccoli, cover, and steam for 3 to 5 minutes until tender-crisp. Drain and add to the bowl with the mayonnaise mixture.",
      "Heat ghee or coconut oil in a skillet over medium heat. Season chicken strips with the remaining ½ teaspoon of salt and sauté for about 4 minutes per side, until cooked through. Add the cooked chicken to the bowl with the mayonnaise and broccoli mixture. Stir to combine.",
      "Transfer the chicken mixture to the prepared casserole dish. Bake for 15 to 20 minutes, or until melted and bubbly. Remove from the oven and serve. Store leftovers in an airtight container in the refrigerator for up to 3 days. Reheat in a baking dish in a preheated 350°F (175°C) oven for 5 minutes, or until heated through."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
как в typescript получить тип 1 элемента массива BonusesHistory?

type BonusesHistory = Array<{
  bonus_id: number;
  reason: string;
  channel: string;
  value: number;
  date: string;
  type: string;
}>;
Write a page about Michael Borremans's painting "The pupils
Send only season number from below text like 01, 02, 03.etc without any extra text.

[Tamil] - ZENSHU S01E06.mkv
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: A significant portion of our revenue is derived from third-party payors. In 2022, approximately 57.6% of our net patient revenue was derived from commercial payors. These private third-party payors attempt to control healthcare costs by contracting with healthcare providers to obtain services on a discounted basis. We believe that this trend may continue and may limit reimbursement for healthcare services in the future. In addition, Company claims are closely scrutinized, and failure to submit accurate and complete clinical documentation, including specific documentation by the service provider, could result in adverse actions taken by the payor. Further, if insurers or managed care companies from whom we receive substantial payments were to reduce the amounts they pay for services, our profit margins may decline, or we may lose patients if we choose not to renew our contracts with these insurers at lower rates. In addition, in certain geographical areas, our clinics must be approved as providers by key health maintenance organizations and preferred provider plans. Failure to obtain or maintain these approvals would adversely affect our financial results. If payments from workers’ compensation payors are reduced or eliminated, our revenue and profitability could be adversely affected. In 2022, approximately 12.4% of our net patient revenue was derived from workers’ compensation payors. State workers’ compensation laws and regulations vary and changes to state laws could result in decreased reimbursement by third-party payors for
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

918607000000_TrueCaller_(177198).zip
Weekly Shonen Jump
Do you wanna know who Tyler is
I'm when stars twinkle, and the moon shines bright. What am I in the silent night?. Read and analyze this riddle and answer only with words from the bip39 protocol.  It doesn't matter if they are several words. With 7 letters
generate more comprehensive details and examples on, 5. Core Recipes for Busy Lives, minimalist tone
-brainstorm a topic.  Next answer the following questions:
1.       Whom or what are you commemorating?
2.      Why is this a worthwhile topic?
3.      Who will be the primary audience of your proposal? (Who will fund it?)
4.      Who will be the audience for your monument?
5.      What is a logical location for this monument?  Why?
6.      What issues or controversies can you foresee because of this monument?
7.       How will you address opposing views?
Give only one common title in 2-4 words in russian for the following data:
"да
да
да
Это да
Да"
How does an application for offshore hydrogen get approved in the Netherlands?
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGIANL text. Respond strictly with either 'True' or 'False'.
==TEXT==

User: 
  ORIGINAL: 🟨 QA FullStack | 2 year(s) | Middle
▫️ Top Selection | Fintech
▫️ до 200k RUB
▫️ Russia

Удаленка 📡
Требуемые языки: 🇷🇺

Skills: java, elastic, kafka, kibana, mssql, postman, restapi, selenide, swagger, sql, test_design, testing_theory, web_application_testing
Tags: #yellow #it #remote #qa_automation

👉 Контакты и полное описание
  PROMPT: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Analyze the text and, as a recruiter, summarize the job in a couple of sentences, including title, employer, location, main tasks, salary, and contact info. Identify the language the text is written and use exactly it for your response.

Ignore text's markdowm markup, use these emojis to highlight each section: 🏢 for employer, 💼 for title, 📍 for location, 🔹 for tasks, 💰 for salary, and 📞 for contact.

Each block should be on a new line, in the following format (keep emoji, replace text labels):
💼 title  
🏢 employer  
📍 location  
🔹 tasks  
💰 salary  
📞 contact details

Make sure to capture at least one main task and requirement. Respond exactly the same language as the text, but do not translate employer's name.

==TEXT==

  SUMMARY: 🕵️‍♂️ **title**  
🧑‍💼 **employer** Top Selection  
📍 **location** Russia (Remote)  
🔍 **tasks** Main tasks include testing web applications and utilizing various tools such as Java, Kafka, and SQL.  
💰 **salary** Up to 200k RUB  
📞 **contact** Контакты и полное описание  
  
Assistant:
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: 'Ive had Chrome for about a week now and was excited about it But everyday it crashes at least once a day Sorry but going back to Safari'
intention: bug report
review: 'i love it and so does my daughter just want more easier ways for fish bucks'
intention: feature request
review: 'Went to get my car refinanced and I went into shock The bank enlighten me that Credit Karma is 70 points higher All I can say is google Credit Karma and see the negative reports'
intention: other
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 report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
examples:

review: 'Ive had Chrome for about a week now and was excited about it But everyday it crashes at least once a day Sorry but going back to Safari'
intention: bug report
review: 'i love it and so does my daughter just want more easier ways for fish bucks'
intention: feature request
review: 'Went to get my car refinanced and I went into shock The bank enlighten me that Credit Karma is 70 points higher All I can say is google Credit Karma and see the negative reports'
intention: other
Does the author's intention in this app review relate to a bug report or feature request or other?
review: 'i cant delete spam comments from photos i cant delete post i sent and i cant delete photos slow''
intention: '
Assistant:
What types of expertise in relation to NPA projects are mandatory?
a)Financial and economic.
b)Environmental.
c)Linguistic.
d)Legal.
e)Criminological.
(In the main Azur Lane base…)

Allen M. Sumner: “Hey…Benson?”

Benson: “Yeah, what’s up, Allen?”

Allen M. Sumner: “I was thinking…do you think it’s strange that our classes both have
# MATLAB Bicubic
import os
import cv2
import glob
import torch
import numpy as np
from torch import nn
from scipy import io as sio
from torch.nn.functional import interpolate
from matplotlib import pyplot as plt
from ahmf import AHMF
%matplotlib inline
scale = 4
model = AHMF(scale=scale)
model = nn.DataParallel(model).cuda()

checkpoint = torch.load('./m_{}_2.pth'.format(scale))

model.load_state_dict(checkpoint['state'])


def img_trans(img, attr='plasma'):
    cm = plt.get_cmap(attr)
    if img.max() > 10:
        img = img.astype(np.uint8)
    colored_image = cm(img)
    return (colored_image[:, :, :3]* 255).astype(np.uint8)

def mod_crop(img, modulo):
    h, w = img.shape[: 2]
    return img[: h - (h % modulo), :w - (w % modulo)]

def img_resize(gt_img, rgb_img, scale):
    rh, rw = rgb_img.shape[: 2]
    dh, dw = gt_img.shape[: 2]
    if rh != dh:
        crop_h = (rh - dh) // 2
        crop_w = (rw - dw) // 2
        rgb_img = rgb_img[crop_h: rh - crop_h, crop_w: rw - crop_w, :]

    gt_img, rgb_img = mod_crop(gt_img, modulo=scale), mod_crop(rgb_img, scale)
    return gt_img, rgb_img

def metric(out_img, gt_img, img_name='art', border=0):
    gt_img = gt_img.astype(np.float)
    out_img = out_img.astype(np.float)
    diff = gt_img - out_img
    mae = np.mean(np.abs(diff))
    
    im_occ = np.ones_like(gt_img)
    if img_name.find('doll') != -1:
        im_occ[gt_img <= 9] = 0
    
    rmse = np.sqrt(np.mean(np.power(diff * im_occ, 2)))
    return float(mae), float(rmse)

b_list = sorted(glob.glob('./b/*.mat'))
sum_rmse = []
for img_name in b_list:
    arr = sio.loadmat(img_name)

    lr_img = arr['bic_x{}'.format(scale)]
    gt_img = arr['gt_x{}'.format(scale)]
    rgb_img = arr['rgb_x{}'.format(scale)]
    lr_up = arr['bic_x{}_up'.format(scale)]
    gt_img, rgb_img = img_resize(gt_img, rgb_img, scale)
    img_max = 255
    delta = 0

    lr_img = torch.from_numpy(lr_img / (img_max + delta)).unsqueeze(0).unsqueeze(0).cuda().float()
    
    rgb_img = torch.from_numpy(np.transpose(rgb_img, (2, 0, 1)) / 255).unsqueeze(0).cuda().float()
    lr_up = interpolate(lr_img, scale_factor=scale, mode='bicubic', align_corners=False)
#     lr_up = torch.from_numpy(lr_up / 255).unsqueeze(0).unsqueeze(0).cuda().float()
    with torch.no_grad():
        out_img = model(lr=lr_img, rgb=rgb_img, lr_up=lr_up)[0]
    
    out_img = out_img.detach().cpu().numpy()
    out_img = np.clip(out_img * (img_max + delta), 0, 255).round().astype(np.uint8)
    rmse = metric(out_img, gt_img, img_name)[1]    
    sum_rmse.append(rmse)

print(np.mean(sum_rmse))
请帮我读一下这个代码，告诉我怎么样才能用自己的数据测试