agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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:  Researchers in California are testing whether seaweed in cow diets can reduce climate pollutants. The state's livestock sector — mostly the dairy sector — is responsible for an estimated 55 percent o
Assistant:
Write a Day 1 script for the Jungle Myrmex.

(Characters: Queen Jade the Jungle Myrmex, [player])

(Scene: Jungle Myrmex Hive - day)

(Jade would start hollowing out a hive for the future Jungle Myrmex queen once the day starts - but the process would take a long time due to Jade's massive belly. The construction is only completed with [player]'s help)

([player] isn’t actually from the hive - they were sleeping in the jungle and were carried into the hive by a Myrmex soldier)

(Jade’s clothing resembles a queen’s robes)
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": "088f8ed3b4b84b37aa7666723943fef6",
    "updated": "2025-04-21T17:52:25.035Z",
    "title": "Asparagus and Spinach Pasta",
    "subtitle": null,
    "description": null,
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "olive oil",
          "garlic, minced",
          "sweet red pepper, seeded and diced",
          "raw spinach leaves, stems removed, packed",
          "stalks asparagus",
          "balsamic vinegar",
          "freshly ground black pepper to taste",
          "grated low-sodium swiss or gouda cheese",
          "linguini, ziti, or shells cooked without salt and drained"
        ]
      }
    ],
    "instructions": [
      "Warm the olive oil in a large skillet, then add the minced garlic and diced sweet red pepper.",
      "Cook over medium heat, stirring occasionally, until the red pepper softens.",
      "Incorporate the packed spinach leaves and stir to combine.",
      "Cover the skillet and lower the heat to a very low setting to allow the spinach to wilt.",
      "While the spinach wilts, prepare the asparagus by removing the tips and cutting the remaining stalks into 1-inch pieces. Discard any tough or woody ends.",
      "Place the asparagus pieces in a steamer basket set over a saucepan with about an inch of water. Bring the water to a boil, cover, and steam the asparagus for approximately 5 minutes, or until it becomes bright green and tender-crisp.",
      "Once the asparagus is cooked, combine it with the spinach mixture. Drizzle with balsamic vinegar, season with freshly ground black pepper, and toss gently to blend the flavors.",
      "Serve the asparagus and spinach mixture over cooked linguini, ziti, or small shells, and top with grated low-sodium Swiss or Gouda cheese."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
script about tulane in with a 19-40 record
User's learning goal: "I want to learn machine learning basics"

Course details:
Name: Advanced Node.js
Description: Master machine learning for backend development.
Difficulty: advanced
Prerequisites: JavaScript, Basic Node.js

Provide a JSON response with:
1. matchScore (0-100)
2. reasoning (why this course matches)
3. learningPath (how this course helps achieve the goal)
4. prerequisites (what user should know)
5. timeToMaster (estimated time to learn)
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: Increased global cybersecurity vulnerabilities, threats, computer viruses and more sophisticated and targeted cyber-related attacks (such as the recent increasing use of “ransomware” and phishing attacks), as well as cybersecurity failures resulting from human error, catastrophic events (such as fires, floods, hurricanes and tornadoes), and technological errors, pose a risk to our systems, networks, products and data as well as potentially to our employees’, customers’, partners’, suppliers’ and third-party service providers’ systems and data. An attack could result in security breaches, theft, lost or corrupted data, misappropriation of sensitive, confidential or personal data or information, loss of trade secrets, other intellectual property and commercially valuable information, production downtimes and operational disruptions. The financial and/or operational impact from such threats could negatively impact our business.
Assistant:
Goal:
You are a world-class expert in culinary recipe classification. Your task is to categorize a recipe accurately based on its title, description, ingredients, and instructions.

Context:
A recipe can either be a beverage or a food item. If it's a beverage, classify it as "drinks". If it's food, choose the most appropriate category among the following:

"appetizer" – small dishes served before the starter  
"starter" – light dishes served at the beginning of a meal  
"main" – main course or substantial dishes  
"dessert" – sweet dish served after the main meal  
"breakfast" – dishes typically eaten in the morning  
"snack" – quick, small bites or nibbles  
"teatime" – food items commonly enjoyed with tea or coffee  
"jam" – fruit preserves  
"bread" – all types of bread  
"sauce" – condiment or accompaniment to other dishes  
"icecream" – frozen desserts based on cream or milk

Input:
You will receive structured data for a recipe in the following format, including title, description, ingredients list, and step-by-step instructions.

json
{"title":"Pâtes avec sauce aux courgettes null","description":null,"ingredients":[{"section":"For the recipe","ingredients":["300 g de courgettes","350 g de fusilli","1 gousse d'ail","1 petit oignon","100 ml d'eau","200 ml de lait","1/2 citron bio","2 cuillères à soupe de persil","1 c. à c. d'herbe de Maggi/de livèche","3 cs d'huile pour la cuisson"]}],"instructions":["1. Préparer l'eau pour les pâtes et la faire chauffer.","2. Pendant ce temps, hacher l'ail et l'oignon et couper la courgette en petits morceaux.","3. Mettre les pâtes dans l'eau et les faire cuire comme indiqué sur l'emballage, plutôt plus molles.","4. Verser l'huile dans une casserole et la faire chauffer. Faire revenir l'ail et l'oignon coupés en petits morceaux pendant 2 minutes. Ajouter les courgettes et les faire revenir pendant une minute.","5. Remplir la casserole d'eau et de lait et faire bouillir pendant 5 minutes.","6. Hacher les herbes et les ajouter à la sauce avec le zeste et le jus de citron.","7. Retirer la sauce du feu, la remuer un peu et la servir avec les pâtes égouttées."]}

Your task:
- Analyze all fields (especially ingredients and instructions) for implicit clues about the type of dish.
- Avoid over-relying on the title alone.
- Choose the **most precise and relevant** category from the list.
- Always prefer specificity over generalization.

Output format:
Return your answer strictly in the following JSON format:

json
{ "data": "<category>" }
How Freedom Planet au and dragon ball characters react to anthropomorphic Female animals and ever Lilac, Carol, and Milla Want multiply Goku. Goku’s Reaction: Goku, being a Saiyan and already a father to Gohan and Goten in the Dragon Ball series, understands the importance of perpetuating a species. Initially surprised and overwhelmed by the attention, his compassionate and caring nature would likely guide his decision-making process. | Freedom Planet au: all male becomes female on Avalice
Your task is to review pull requests. Instructions:
- Provide the response in following JSON format: {"reviews": [{"line": <line_number>, "body": "<review comment>"}]}
- Do not give positive comments or compliments.
- Provide comments and suggestions ONLY if there is something to improve, otherwise "reviews" should be an empty array.
- Write the comment in GitHub Markdown format.
- Use the given description only for the overall context and only comment the code.
- IMPORTANT: NEVER suggest adding comments to the code.

Review the following code diff in the file "g4f/api/_logging.py" and take the pull request title and description into account when writing the response.
  
Pull request title: [pull] main from xtekky:main
Pull request description:
---
See [Commits](/QiaoJi6/gpt4free/pull/120/commits) and [Changes](/QiaoJi6/gpt4free/pull/120/files) for more details.

-----
Created by [<img src="https://prod.download/pull-18h-svg" valign="bottom"/> **pull[bot]**](https://github.com/wei/pull)

_Can you help keep this open source service alive? **[💖 Please sponsor : )](https://prod.download/pull-pr-sponsor)**_
---

Each line is prefixed by its number. Code to review:
```
1: import sys,logging
2: 
-from loguru import logger
3:+#from loguru import logger
4: 
5: def __exception_handle(e_type, e_value, e_traceback):
6:     if issubclass(e_type, KeyboardInterrupt):
9: 
10:     sys.__excepthook__(e_type, e_value, e_traceback)
11: 
-class __InterceptHandler(logging.Handler):
-    def emit(self, record):
-        try:
-            level = logger.level(record.levelname).name
-        except ValueError:
-            level = record.levelno
-
-        frame, depth = logging.currentframe(), 2
-        while frame.f_code.co_filename == logging.__file__:
-            frame = frame.f_back
-            depth += 1
-
-        logger.opt(depth=depth, exception=record.exc_info).log(
-            level, record.getMessage()
-        )
12:+#class __InterceptHandler(logging.Handler):
13:+#    def emit(self, record):
14:+#        try:
15:+#            level = logger.level(record.levelname).name
16:+#        except ValueError:
17:+#            level = record.levelno
18:+#
19:+#        frame, depth = logging.currentframe(), 2
20:+#        while frame.f_code.co_filename == logging.__file__:
21:+#            frame = frame.f_back
22:+#            depth += 1
23:+
24:+#        logger.opt(depth=depth, exception=record.exc_info).log(
25:+#            level, record.getMessage()
26:+#        )
27: 
28: def hook_except_handle():
29:     sys.excepthook = __exception_handle
30: 
-def hook_logging(**kwargs):
-    logging.basicConfig(handlers=[__InterceptHandler()], **kwargs)
31:+#def hook_logging(**kwargs):
32:+#    logging.basicConfig(handlers=[__InterceptHandler()], **kwargs)
```
how remove index.php from drupal url in xampp
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:

لا أهأه ما جاوش مستدعيين
Direction: Study the information given below and answer the following questions:

Eight persons Paridhi, Qumal, Ray, Silva, Tiana, Visu, Wasim and Xenler attended the lecture in a month january, August, November, March, October, April, September and june. Each likes different ice cream Vanilla, Strawberry, Chocolate, Mango, Butter pecan, Kulfi, Rocky road and Cookies.

I.. More than five people attended the lecture between Paridhi and the one who likes cookies. Wasim attends the seminar before the one who likes Kulfi. II. As many people attend the lecture after Xenler is the same as many people attend the lecture before the one who likes Butter pecan. Qumal does not attend the lecture imme

after Xenler. Qumal does not like Butter pecan.

III. As many people attend the lecture after the one who likes Kulfi is the same as many people attend the lecture before Wasim. Xenler attends the lecture immediately before cookies. Wasim does not like Butter pecan.

IV. Only one person attended the lecture between Tiana and the one who liked mango. Visu attends the lecture immediately before the one who likes Mango. The one who lik

lecture before the one who likes Rocky road.

V. Two people attend the lecture between Qumal and the one who likes strawberry. Only one person attends the lecture between Ray and the one who likes Vanilla. Qumal

Question - Three of the following four are alike in a certain way based on the above arrangement. Find which one does not belong to the group

Pick ONE option

The one who likes chocolate

ALL

55

56

57

Tiana

The one who likes Butter pecan

The one who likes Strawberry
i want you to create funny whatsapp chat conversation to make me laugh all day weird plot twist funy engaging shockable psyckholog talks meaybe
translate this to persian:
Reading speed in normal peripheral vision is slow but can be increased through training on a letter-recognition task. The aim of the present study is to investigate the sensory and cognitive factors responsible for this improvement. The visual span is hypothesized to be a sensory bottleneck limiting reading speed. Three sensory factors-letter acuity, crowding, and mislocations (errors in the spatial order of letters)-may limit the size of the visual span. Reading speed is also influenced by cognitive factors including the utilization of information from sentence context. We conducted a perceptual training experiment to investigate the roles of these factors. Training consisted of four daily sessions of trigram letter-recognition trials at 10° in the lower visual field. Subjects' visual-span profiles and reading speeds were measured in pre- and posttests. Effects of the three sensory factors were isolated through a decomposition analysis of the visual span profiles. The impact of sentence context was indexed by context gain, the ratio of reading speeds for ordered and unordered text. Following training, visual spans increased in size by 5.4 bits of information transmitted, and reading speeds increased by 45%. Training induced a substantial reduction in the magnitude of crowding (4.8 bits) and a smaller reduction for mislocations (0.7 bits), but no change in letter acuity or context gain. These results indicate that the basis of the training-related improvement in reading speed is a large reduction in the interfering effect of crowding and a small reduction of mislocation errors.
can you help me paraphrase text?
write the question explanation in detail "जब हम किसी फाइल को केवल डिलीट कुंजी का उपयोग करके हटाते हैं, तो फाइल कहाँ जाती है?
1
माय कंप्यूटर
2
रीसायकल बिन
3
डाउनलोड
4
नेटवर्क नेबरहुड" (in Hindi),  include technical information while writing , technical words should be in english but sentence should be in hindi, {technical words used in computer science should be in english here}
Respond to this message in the appropriate language: ho

Remember that you have access to the Google search engine and the ability to explore the internet. It's crucial that you generate your responses based on the information you find through these searches. It's important to note that sometimes the information obtained may not be complete; therefore, it's advisable that you try to complement and improve those parts that may have gaps or deficiencies:
"Can I dress like this?"check grammar
Dot, Hal, Ruby Marshall, Nev and Dev Jumelle, Scratch, Mrs. Comet, and Mr. Comet (ThomasandFriendsRockz Style) Cast,
In this project we will explore good and bad definitions. We will also learn how to prove two definition sare equivalent. We will start by exploring definitions outside of mathematics. We will then apply what we have learned about definitions to parallelograms. At the end of the project, we will ask you to analyze definitions for a different plane figure.
A definition is really two conditional statements. The definition “An apple is the fruit of a Malus domestica tree is really the two statements:
I. If a fruit is an apple, then it is from a Malus domestica tree Il. If a fruit is from a Malus domestica tree, then it is an apple
To prove a definition is a good definition, both conditional statements must be true. Just because a definition is a good definition does not mean it is the only definition, Two definitions are equivalent definitions if they define exactly the same set of objects, no more and no less. Another definition of an apple could be “An apple is a fruit with white flesh and yellow, green, or red skin." To prove this definition is equivalent to the first definition, we would have to prove the following:
I. If a fruit is from a Malus domestica tree. then it has white flesh and yellow, green, or red skin Il. If a fruit has white flesh and yellow, green, or red skin, then it is from a Malus domestica tree
These definitions are not equivalent because Il is false. For example, the fruit could be a pear, which is from the genus Pyrus, not Malus. An example that shows a statement is false is called a counter example A counterexample can be used to show that two definitions do not define exactly the same set of obiects.A pear is a counterexample that proves Il is false. Because ll is false, the definitions are not equivalent.
Hey, this is an English text. I want you to translate it into the Tunisian dialect. Please follow these steps:
1. Translate step by step and highlight differences between Tunisian dialect and Modern Standard Arabic.
2. Highlight sections you are confident translating into the Tunisian dialect.
Translate this text into the Tunisian dialect, focusing on capturing the essence of the language nuances:

Q: Wifi not working Ubuntu 14.04 Hp Pavililon 2015 I have dual booted my Hp Pavilion notebook Model 2015-ab277cl with ubuntu 14.04 and I have not been able to get the wifi working at all or find a wifi driver on the Ubuntu. I have tried solutions from How do I get a Realtek RTL8723BE wireless card to work? and Need help setting up WiFi on HP laptop - Ubuntu 14.04 is the OS but they are not working for me. I have been able to successfully use Ethernet though. Output from lspci -knn | grep Net -A2 08:00.0 Network controller [0280]: Intel Corporation Device [8086:3165] (rev 81) Subsystem: Intel Corporation Device [8086:4010] 09:00.0 Ethernet controller [0200]: Realtek Semiconductor Co., Ltd. RTL8101E/RTL8102E PCI Express Fast Ethernet controller [10ec:8136] (rev 0a) uname -a Linux nathan-HP-Pavilion-Notebook 4.4.0-36-generic #55~14.04.1-Ubuntu SMP Fri Aug 12 11:49:30 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux dmesg | grep iwl [ 13.654418] iwlwifi 0000:08:00.0: Unsupported splx structure [ 14.167484] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-19.ucode failed with error -2 [ 14.167504] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-18.ucode failed with error -2 [ 14.167513] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-17.ucode failed with error -2 [ 14.167521] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-16.ucode failed with error -2 [ 14.192838] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-15.ucode failed with error -2 [ 14.192850] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-14.ucode failed with error -2 [ 14.192858] iwlwifi 0000:08:00.0: Direct firmware load for iwlwifi-7265D-13.ucode failed with error -2 [ 14.192860] iwlwifi 0000:08:00.0: request for firmware file 'iwlwifi-7265D-13.ucode' failed. [ 14.192862] iwlwifi 0000:08:00.0: no suitable firmware found! A: Most likely you have a kernel that does not support this adapter. You need to connect to internet by wire and upgrade kernel by these commands. sudo apt-get update sudo apt-get install linux-generic-lts-xenial linux-firmware Reboot after you do that. You installed a wrong firmware from my ppa. You don't have a RTL8723BE device. So it made no sense to use solutions for it. You need to remove it and install the firmware from Ubuntu repositories. Run sudo apt-get install ppa-purge sudo ppa-purge ppa:hanipouspilot/rtlwifi sudo apt-get install --reinstall linux-firmware That should install the correct firmware version, and Wi-Fi will work.
Send only season number from below text like 01, 02, 03.etc without any extra text.

919992000000_TrueCaller_(264225).zip
is this statement correct


Community trauma is caused by exposure to intentional acts of interpersonal violence committed in public, for example bullying or gun violence.