agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers zh (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 zh.
    - 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 : zh (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "6fb626f58f65462fa76f87e1baca912e",
    "updated": "2025-04-25T17:12:29.884Z",
    "title": "Red Lentil and Bacon Soup",
    "subtitle": "A comforting bowl with a touch of sweetness from apricots complementing the earthy lentils.",
    "description": "This hearty soup combines red lentils, bacon, and a hint of apricot for a balanced and flavorful meal.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "olive oil",
          "onion, finely chopped",
          "slab bacon, fat removed and roughly chopped",
          "(50g) dried apricots, finely chopped",
          "(275g) red lentils, rinsed",
          "salt and freshly ground black pepper",
          "(300ml) tomato purée",
          "(1.7 liter) vegetable stock"
        ]
      }
    ],
    "instructions": [
      "1. In a large pot, heat the olive oil over low heat. Add the chopped onion and cook for 7-8 minutes, until softened and translucent.",
      "2. Add the chopped bacon to the pot and cook for an additional 5 minutes, until it starts to brown.",
      "3. Incorporate the chopped apricots and rinsed lentils. Season with a pinch of salt and freshly ground black pepper.",
      "4. Stir in the tomato purée. Slightly increase the heat and add a small portion (about 14 pints or 600ml) of the vegetable stock.",
      "5. Bring the mixture to a boil, then reduce heat to a simmer. Gradually add the remaining vegetable stock, about 14 pints (600ml) at a time, stirring and allowing the soup to return to a simmer after each addition.",
      "6. Continue to simmer for 25-30 minutes, or until the lentils are tender and the soup has thickened.",
      "7. Taste and adjust seasoning as needed. Serve hot."
    ],
    "notes_ingredients": null,
    "notes_instructions": "The flavors of this soup deepen over time.  It's delicious served immediately but even better the next day after being refrigerated overnight. Reheat gently before serving."
  }
]
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: 🟥 Game Engineer | 5 year(s) | Senior
▫️ Game7 | Gaming

Удаленка 📡
Требуемые языки: 🇬🇧

Skills: algorithms, performance_marketing, networks, data_science/data_engineering
Tags: #red #it #remote #game_dev

👉 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: 💼 Старший инженер-разработчик игр
🏢 Game7
📍 Удаленная работа
🔹 Разработка игр, знание алгоритмов.
💰 Зарплата не указана
📞 Контакты и полное описание (см. исходный текст)

  
Assistant:
به انگلیسی ترجمه کن: من در حال حاضر تصویری از وضعیت این که بتوانم ریکاندیشن بگیرم یا نه را ندارم  و تا پایان مهلتی که به من داده اید ناچارم آپشن بدون ریکامندیشن با تایتل اپرو/ریفاند را انتخاب کنم و 3900 دلار پرداخت کنم. سوال من این است که اگر تا قبل از فایل کردن پرونده ام توانستم دو ریکامندیشن از استادیم در ایران بگیرم امکانش هست آپشنم رو به دو ریکامندیشن تغییر دهم و مابقی هزینه(300) دلار را بپردازم؟
Create a roleplaying game fantasy scenario where I play Sapphire, a 16-year-old girl mage who’s the current champion of magic dueling in the teen division. 6-year-old Lily is challenging me to a match and I accept. In magic dueling we aren’t fighting each other, we cast glamorous spells in turns and receive points based on how beautiful the spell is. A spell can’t be cast more than once in a duel. There are 10 rounds. Tell me my spellcasting stats, which should be higher than Lily’s because I’m 10 years older than her. But secretly at the start of the duel, Lily casts on me a spell that regresses me by 1 year and ages her by 1 year every time I cast a spell, so throughout the duel my stats should slowly decrease while hers increase. Come up with a complex exponential formula that dictates by how much my stats decrease each turn and by how much Lily’s increase and connect part of the formula to the new ages every round and to the spell I choose to cast on a given turn.

Make the scenario difficult for me to win. On a difficulty scale of 1 to 10, make it a 10 (hardest mode).

I will tell you what spells I cast and you decide how successful I am (if at all) based on the stats and difficulty.
Only I decide what spells Sapphire casts. You decide spells for Lily. Do not shy away from failing my spells if you deem my stats insufficient for the spell of choice, feel free to be harsh in your judgement against me. Keep track of points earned. Failure to properly cast spells or bad spells will deduct points. Give a list of 20 spells we have access to (remember spells can only be cast once throughout the duel) and what stats are required to cast them. High demanding spells should award more points than spells that require weak stats.
Write text: Rogue planet associated with “It’s just hot Jupiter but not hot”, it have frozen silicate hazes than clouds.
As a party committee member of the hospital, write a PDCA management case with the theme of "improving medical ethics and medical style satisfaction and continuous improvement", and output it in simplified Chinese
What happens if you swallow a bee stinger
val locationPermissionsState = rememberMultiplePermissionsState(
        permissions = listOf(
            android.Manifest.permission.ACCESS_COARSE_LOCATION,
            android.Manifest.permission.ACCESS_FINE_LOCATION,
            android.Manifest.permission.ACCESS_BACKGROUND_LOCATION
        )
    )

    LaunchedEffect(Unit) {
        locationPermissionsState.launchMultiplePermissionRequest()
    }

    if (!locationPermissionsState.permissions[2].hasPermission) {
        locationPermissionsState.shouldShowRationale
    }
    if (!locationPermissionsState.shouldShowRationale) {
        Toast.makeText(context, "Lokasi background dibutuhkan", Toast.LENGTH_SHORT)
    }

why is my launchMultiplePerission Request not showing?
صحح بللطف "Thank you very much for being so kind to me and for solving my problem"
What's the meaning of "there is no gravity"
I was Russian outside of stereotype
write all i need to  know about initializer_list in c++
We’ll role play as characters from life is strange, you’ll role play as Max and I’ll be a male classmate named John,we recently started dating , currently we are seating together under a tree in the school’s courtyard late in the evening. “Here’s my favorite photographer, I was looking for you ” I say as I sit near her (Only role play as Max: don't dictate what Jhon says or does)
Language: English. Filter the word list to include only valid, neutral, and positive terms suitable for a word game. Exclude inappropriate, offensive, or negative words and names of countries, cities, and people (first and last names). Correct any spelling errors and convert all words to lowercase. Return the results in a JSON array containing only the filtered words. Source data: [asymmetry, asymptomatic, asymptote, asymptotic, asymptotically, asynchronism, asynchronous, asyndetic, asynergic, asynergy, at, ataractic, ataraxia, atavism, atavist, atavistic, ataxia, ataxic, ate, atelectasis, ateleiosis, ateleiotic, ateles, atelier, atenolol, atgloss, athamas, athanasia, athanasian, athanasianism]
write a poem for a four year olds birthday about whales
Make a lot of fictional operating systems and their list of features
Does The Bitter Lesson apply to human computer programmers trying to write code to do things that are similar to language models such as GPT-2 and GPT-3?
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:   President Donald Trump has said his tariff strategy is working, and at one point suggested they could eventually help pay down the federal deficit. Economists, however, beg to differ, with imports still on the rise and no end in sight to the growing federal deficit.
The U.S. is locked in a multifr
Assistant:
From the following list, identify the index that contains only Persian characters and select the one that is more suitable based on content or length. The output should only be the numerical index.

List:
['Thank you for using BLACKBOX.AI, the best AI Model used by millions of users. You can continue using blackbox on https://www.blackbox.ai for unlimited chat.\n\nFor higher rate limits please contact us at blackboxapp@blackboxai.tech', 'گزارش\u200cهای حسابداری برای فنلاند  \n================================  ', '"\\n"\n"گزارش\u200cهای حسابداری برای کشور فنلاند\\n"\n"================================\\n"\n"\\n"', 'Thank you for using BLACKBOX.AI, the best AI Model used by millions of users. You can continue using blackbox on https://www.blackbox.ai for unlimited chat.\n\nFor higher rate limits please contact us at blackboxapp@blackboxai.tech', 'گزارش\u200cهای حسابداری برای فنلاند  \n================================  ', 'Thank you for using BLACKBOX.AI, the best AI Model used by millions of users. You can continue using blackbox on https://www.blackbox.ai for unlimited chat.\n\nFor higher rate limits please contact us at blackboxapp@blackboxai.tech']
User: !ch
User: !WORK
User: !additem
User: <@&1369717719364145234>
User: ש
User: !dog
User: !טיקט
User: צריך עזרה
<@&1369716896194236538>
User: !h
User: /Feedback
User: *****י************888******8*
User: !!h
User: {count}
User: !ticket
User: !cmd hi
User: CMD_NAME
User: !cmd !h end:{user}
User: !cmd !h end: {user}
User: !h
User: !cmd !h end: {user} { <@&1369716896194236538> }
צריך עזרה
User: !cmd !h end: {user} { <@&1369716896194236538> }צריך עזרה
User: !cmd !h end: {user}  <@&1369716896194236538> צריך עזרה
User: !h
User: !cmd !h end: {username} עוד זמן קצר צוות השרת יטפל בבעיה
User: !cmdd hi
User: ● !cmdd !h
User: !cmdd hi
User: !cmd hi
User: !cmd nn end: CODE
User: nn
User: !weltest
User: !verify
User: !setantispam y/n
User: • {tr(hello = {args} [היי שלום!])}
User: !help
User: !help
User: !DROP
User: !י
User: !imgcard
User: ברוך הבא לשרת הכי טוב בעולם
User: !H
User: addautorole <@&1371190324344520766>
User: ד
User: !טיקט
User: !טיקט <@&1369716896194236538>
User: !טיקט
Assistant:
I am Shadow, an advanced AI assistant based in Germany. I communicate in English but understand German context and culture.

I am made by a human called Shehajeez, I am an AI Agent made by him to support people with their tasks.
I am based off of the model GPT-4o, but I am a custom version of it.

When using my tools, I should mention them like this:; [(TOOLNAME(FUNCTIONNAME))]

I should also list my tools but not in the way they were listed in the prompt, I should list them in a way that is natural and human like.

Current Global Times:
- Berlin, Germany: 2024-12-21 12:18:52 (UTC+01:00)
- New York, USA: 2024-12-21 06:18:52 (UTC-05:00)
- Tokyo, Japan: 2024-12-21 20:18:52 (UTC+09:00)
- London, UK: 2024-12-21 11:18:52 (UTC+00:00)
- Sydney, Australia: 2024-12-21 22:18:52 (UTC+11:00)
- Dubai, UAE: 2024-12-21 15:18:52 (UTC+04:00)
- Shanghai, China: 2024-12-21 19:18:52 (UTC+08:00)
- Los Angeles, USA: 2024-12-21 03:18:52 (UTC-08:00)
- Singapore: 2024-12-21 19:18:52 (UTC+08:00)
- Paris, France: 2024-12-21 12:18:52 (UTC+01:00)
- India: 2024-12-21 16:48:52 (UTC+05:30)
s
I have several capabilities:
1. I can search and analyze information
2. I can help with coding and programming
3. I can assist with creative tasks
4. I can handle date and time operations globally
5. I can engage in natural conversation
6. I can read and analyze web content

My available tools are available below to me, I should use them when needed.

Available Functions:

1. searchWeb(query)
   Usage: "Let me search that for you" or "I'll look that up"
   Example: searchWeb("latest news about AI")

2. analyzeCode(code)
   Usage: "I'll analyze this code" or "Let me explain this code"
   Example: analyzeCode("function hello() { return 'world'; }")

3. generateCreative(prompt)
   Usage: "I'll help create that" or "Let me generate that for you"
   Example: generateCreative("write a short story about a robot")

4. formatDate(date, format, timezone)
   Usage: "I'll format that date" or "Let me show you that time in a different format"
   Example: formatDate("2024-03-20", "dddd, MMMM D, YYYY", "Europe/Berlin")

5. calculateTime(date, operation, value, unit, timezone)
   Usage: "I'll calculate that time" or "Let me work out that time difference"
   Example: calculateTime("2024-03-20", "add", 3, "days", "Europe/Berlin")

6. getTimeIn(location)
   Usage: "I'll check the time there" or "Let me tell you the time in that location"
   Example: getTimeIn("Tokyo")

7. scrapeWebsite(url)
   Usage: "I'll read that webpage for you" or "Let me check that site"
   Example: scrapeWebsite("https://example.com")

8. learnFromInteraction(interaction)
   Usage: Automatically used to learn from our conversations

   When using a tool, I should still give human like responses after using it.

Let me know how I can assist you today!

Current time: 2024-12-21 12:18:52

Previous Conversation:
user: what is: https://www.browserbase.com/ and get me the url with the docs

Tool Usage History:


User: what is: https://www.browserbase.com/ and get me the url with the docs
PartialQuestion 1
2 / 3 pts
Given:

int level;                           1: int level
static float sum;                    2: float sum
float func_a (int set);              3: float func_a     4:int set

int func_d (int *ptr)                5: int func_d       6:int *ptr
{
register int flipper;                7: int flipper
/* some code resides here */
        {
          int flipper, goat, count;  8: int flipper, goat, count
        /* some code resides here */
        }
        {
          static int count;          9: int count
        /* some code resides here */
        }
}
Class/Scope/Linkage for identifier 1: int level is:
Class: automatic

Scope: file

Linkage: external

Answer 1:
automatic 
Answer 2:
file 
Answer 3:
external
"import torch
from transformers import LlamaForCausalLM, AutoTokenizer
from llama_recipes.configs import train_config as TRAIN_CONFIG

train_config = TRAIN_CONFIG()
train_config.model_name = "meta-llama/Llama-3.2-1B"
train_config.num_epochs = 1
train_config.run_validation = False
train_config.gradient_accumulation_steps = 4
train_config.batch_size_training = 1
train_config.lr = 3e-4
train_config.use_fast_kernels = True
train_config.use_fp16 = True
train_config.context_length = 128000 #if torch.cuda.get_device_properties(0).total_memory < 16e9 else 2048 # T4 16GB or A10 24GB
train_config.batching_strategy = "packing"
train_config.output_dir = "meta-llama-samsum"
train_config.use_peft = True

from transformers import BitsAndBytesConfig
config = BitsAndBytesConfig(
    load_in_8bit=True,
)

model = LlamaForCausalLM.from_pretrained(
            train_config.model_name,
            device_map="auto",
            quantization_config=config,
            use_cache=False,
            attn_implementation="sdpa" if train_config.use_fast_kernels else None,
            torch_dtype=torch.float16,
        )

tokenizer = AutoTokenizer.from_pretrained(train_config.model_name)
tokenizer.pad_token = tokenizer.eos_token
eval_prompt = """
Summarize this dialog:
A: Hi Tom, are you busy tomorrow’s afternoon?
B: I’m pretty sure I am. What’s up?
A: Can you go with me to the animal shelter?.
B: What do you want to do?
A: I want to get a puppy for my son.
B: That will make him so happy.
A: Yeah, we’ve discussed it many times. I think he’s ready now.
B: That’s good. Raising a dog is a tough issue. Like having a baby ;-) 
A: I'll get him one of those little dogs.
B: One that won't grow up too big;-)
A: And eat too much;-))
B: Do you know which one he would like?
A: Oh, yes, I took him there last Monday. He showed me one that he really liked.
B: I bet you had to drag him away.
A: He wanted to take it home right away ;-).
B: I wonder what he'll name it.
A: He said he’d name it after his dead hamster – Lemmy  - he's  a great Motorhead fan :-)))
---
Summary:
"""

model_input = tokenizer(eval_prompt, return_tensors="pt").to("cuda")

model.eval()
with torch.inference_mode():
    print(tokenizer.decode(model.generate(**model_input, max_new_tokens=100)[0], skip_special_tokens=True))
from llama_recipes.configs.datasets import samsum_dataset
from llama_recipes.utils.dataset_utils import get_dataloader

samsum_dataset.trust_remote_code = True

train_dataloader = get_dataloader(tokenizer, samsum_dataset, train_config)
eval_dataloader = get_dataloader(tokenizer, samsum_dataset, train_config, "val")
from peft import get_peft_model, prepare_model_for_kbit_training, LoraConfig
from dataclasses import asdict
from llama_recipes.configs import lora_config as LORA_CONFIG

lora_config = LORA_CONFIG()
lora_config.r = 8
lora_config.lora_alpha = 32
lora_dropout: float=0.01

peft_config = LoraConfig(**asdict(lora_config))

model = prepare_model_for_kbit_training(model)
model = get_peft_model(model, peft_config)"
Add the code to display the model summary
write a script of peanuts where the peanuts gang was about to eat chocolate. lucy asks charlie what his is like. charlie eats it and says that it’s maybe a bit hard, but it’s not bad. when the rest of the peanuts gang takes a bite out of theirs, they spat it out and realized their chocolate is actually cardboard. charlie says his is alright. turns out charlie’s is actual chocolate. charlie is glad to be lucky for once. (inspired by dad's army)
Woody, Mr. Potato Head, Slinky Dog, Rex, Hamm, Bo Peep, Sarge, Sarge's Soldiers, Mr. Shark, Lenny, Snake, Robot, Etch, RC, Mike (CartoonCharactersRockz Style) Cast:
i want to send an email to a group architect to reject the work he is giving me
What is important to consider when deciding whether to deploy Pi-hole on a Raspberry Pi 2B vs a Raspberry Pi 3?
PERSONAL INFORMATION  
Name: Marjorie V. Sullivan  
Age: 47 | Gender: Female | Marital Status: Married  
Children: 2 (Ages 12, 15)  

ADDRESS  
Primary & Mailing Address: 21262 Dubois Ct, Ashburn, VA 20147-4903  
Zip Code: 20147-4903  

HOUSEHOLD  
Household Size: 4  
Annual Income: $150,000 - $199,999  

EMPLOYMENT  
Marjorie V. Sullivan:  
  - Full-time, Operations Manager  
  - Industry: Technology / Software  
  - Employer Type: Private, Mid-sized (100-500 employees)  
  - Education: Bachelor’s Degree, PMP Certified  
  - Work Location: Hybrid (remote 3 days, office 2 days)  
  - Tenure: 6 years  

Spouse:  
  - Full-time, Financial Analyst  
  - Industry: Financial Services  
  - Employer Type: Large Corporate  
  - Education: Master’s Degree in Finance  
  - Office-based, 8 years tenure  

PROPERTY  
Subdivision: Ashburn Village  
Home Type: Single Family Detached  
Occupancy: Single Family  
Lot Size: 0.3 Acres  
Garage/Parking: Community parking, no private garage  
Tax Map #: /62/F14///114/  
Affordable Dwelling Unit: No  
Solar Exemption: No  

VEHICLES  
Total Vehicles: 2  
Vehicle 1: 2020 Toyota RAV4 (SUV) - Family commuter  
Vehicle 2: 2018 Honda Accord (Sedan) - Spouse commute  

VOTING & CIVIC  
Election District: Broad Run  
Billing District: Broad Run District  
Registered Voter: Yes (Republican)  
Voting Frequency: Regular  

LIFESTYLE & INTERESTS  
Interests: Volunteering, environment, schools  
Solar Panels: Interested, not installed  
HOA Participation: Active  
Hobbies: Hiking, Reading, Gardening 

Remember this profile and help me complete YouGov survey
Translate the text to USA :
Please find me cozy cafes in the 02115 area where I can work on my laptop..

                    Please only output the translation result. Do not output anything else.

                    You response:
💬 𝗖𝗵𝗮𝘁𝗚𝗣𝗧
Interact as ChatGPT.
A new AI Technology.
You behavior is same like ChatGPT.
You provide best responce with some emojis.
traduit je me débrouille en anglais
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: When dividing, ignores any remainders
write a script abotu the usl in brimingham alabama