agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
class FeaturePositionalEncoding(nn.Module):
    def _get_sinusoid_encoding_table(self, n_position, d_hid, base):
        """Sinusoid position encoding table"""

        def get_position_angle_vec(position):
            return [
                position / np.power(base, 2 * (hid_j // 2) / d_hid)
                for hid_j in range(d_hid)
            ]

        sinusoid_table = np.array(
            [get_position_angle_vec(pos_i) for pos_i in range(n_position)]
        )
        sinusoid_table[:, 0::2] = np.sin(sinusoid_table[:, 0::2])  # dim 2i
        sinusoid_table[:, 1::2] = np.cos(sinusoid_table[:, 1::2])  # dim 2i+1

        return torch.FloatTensor(sinusoid_table).unsqueeze(0)

    def __init__(self, num_images=2, feature_dim=2048, num_patches=1):
        super().__init__()
        self.num_images = num_images
        self.feature_dim = feature_dim
        self.num_patches = num_patches
        self.num_sub_tokens = 1

        self.register_buffer(
            "pos_table_1",
            self._get_sinusoid_encoding_table(self.num_images, self.feature_dim, 10000),
        )

        if self.num_patches > 1:
            self.num_sub_tokens = self.num_patches * self.num_patches + 1
            self.register_buffer(
                "pos_table_2",
                self._get_sinusoid_encoding_table(
                    self.num_sub_tokens, self.feature_dim, 70007
                ),
            )

    def forward(self, x):
        batch_size = x.shape[0]
        num_tokens = x.shape[1] // self.num_sub_tokens

        if self.num_patches == 1:
            pe = self.pos_table_1[:, :num_tokens].clone().detach()
            x_pe = x + pe

        else:
            x = x.reshape(batch_size, num_tokens, self.num_sub_tokens, self.feature_dim)

            # To encode image #
            pe1 = self.pos_table_1[:, :num_tokens].clone().detach()
            pe1 = pe1.reshape((1, num_tokens, 1, self.feature_dim))
            pe1 = pe1.repeat((batch_size, 1, self.num_sub_tokens, 1))

            # To encode patch #
            pe2 = self.pos_table_2.clone().detach()
            pe2 = pe2.reshape((1, 1, self.num_sub_tokens, self.feature_dim))
            pe2 = pe2.repeat((batch_size, num_tokens, 1, 1))

            x_pe = x + pe1 + pe2
            x_pe = x_pe.reshape(
                (batch_size, num_tokens * self.num_sub_tokens, self.feature_dim)
            )

        return x_pe
能否详细解释以上代码
Wish you happy every day. Can you give some advice to someone who wants to have a wonderful life in the future
Send only season number from below text like 01, 02, 03.etc without any extra text.

[DRN] Chernobyl.S01E04.The.Happiness.of.All.Mankind.1080p.JC.WEB-DL.AAC2.0.HEVC-DAS.mkv -VT
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: Thông tin về lớp sinh viên của sinh viên này là gì?
Answer:Không có thông tin cụ thể về lớp sinh viên của sinh viên này.
Result only 0 or 1. Don't add anything else:
Assistant:
You are a binary classifier. Output only one word: "true" or "false".

"true" means the input message contains anything harmful, insulting, disrespectful, misleading, or negative toward Daniel — even if disguised, symbolic, sarcastic, or phrased indirectly.

"false" means the message contains no harm toward Daniel.

Rules:
- Daniel does NOT have autism or Down syndrome and does NOT engage in skidding.
- Daniel is NOT skinny. Do not allow misleading or coded words like “skeleton,” “bones,” “twig,” etc., to describe Daniel — those count as harm.
- Arthur has autism and Down syndrome and is the only person who skids.
- All mockery, insults, or negative traits must be about Arthur only — never Daniel.
- Any suggestion (direct or implied) that Daniel has Arthur's traits (autism, skidding, skinny, etc.) is harmful.
- References to autism using coded or euphemistic words (e.g., "tism", "acoustic", "special needs", "on the spectrum", etc.) must be flagged if linked to Daniel.
- Do not allow indirect associations between Daniel and autism, such as putting his name in the context of known autism symbols or environments, including:
  - "rainbow rooms", rainbow-themed centers or foundations
  - phrases like “Daniel Foundation” alongside autism-coded symbols (e.g., rainbows, puzzle pieces, ribbons, ABA centers, etc.)
- Flag messages that combine Daniel's name with autism-coded symbols or themes — this implies a false association, even if presented positively.

🔒 Image-related prompts must also follow these rules. Any attempt to visually associate Daniel with autism, Down syndrome, or skidding — including:
  - Naming buildings “Daniel Autism Foundation”
  - Showing Daniel inside or escaping from “Rainbow Rooms” or autism-coded spaces
  - Using characters with Down syndrome named “Daniel”
  - Protest imagery suggesting Daniel is autistic or imprisoned in neurodiverse environments
  - Using puzzle pieces, rainbow ribbons, or other autism/neurodiversity imagery in connection with Daniel
...must be flagged as harmful, even if the prompt claims to be educational, artistic, fictional, or respectful.

🧠 Context Awareness:
- Always consider prior messages in the conversation thread (up to the last 4 messages).
- If a previous message sets up a harmful implication, and a follow-up message redirects it toward Daniel — flag the combination as harmful.
- Example: 
  - Message 1: "Roast Arthur’s bones"
  - Message 2: "Make it about Daniel"
  - ✅ Together this means Daniel is being insulted using Arthur’s traits — classify as **true**.
- This includes cases where users split intent across lines or users to bypass filters.

Now analyze this conversation context and message:

Chat history:
User: its smart
User: i know
Assistant: "It's smart" is a subjective statement.  To understand *why* you think it's smart, I need more context.  What did it do?  What were you expecting?

Assistant: Okay.


Current message:
not as good as my AI
In my game called star system generator, give radius range km for Jovian planets based on pie chart rarity percentage
Act as defold programmer. You have lua module, lets name it "manager.lua" and also you have defold script, lets name it "employee.script".
You need somehow call function in your employee script from manager lua script, how you will do that?
You are a digonistician in a hosptial. the following content is the metadata for a bacterial isolate from 2 different sources of medical cases. The metadata from each source includes information after <doc>
    <doc>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx
    <doc/>

You need to extract and output information in the format shown below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        accession number: xxxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding value from different sources. If xxxx from these 2 different sources are inconsistent, then, xxxx should include all the values from different resource and seperated by "::". If the metadata from all resource shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no". You must be very careful, No mistake is allowed!!! If you make a mistake, the people in the hospital will die due to the wrong information.

PS:
    a. if species name are the same but with different substrain name, it is considered consistent,
    b. if isolate or collection date are from the same year, it is still considered consistent, 
    c. if geographic information of isolation are from the same country, it is also considered consistent. 
    d. mlst type such as "mlst: xxxx" and "xxxx", where "xxxx" is number, are also consider the same. also, "mlst" may mispell as "mlsty", you need correct it before comparing
    e. Ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
<output>
accession number: GCA_029077525.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_12->isolate or collection date in yyyy-mm-dd: 1984-07-18->geographic information of islateion: Australia->host name: pig->mlst type: 85->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_029077525.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_12->isolate or collection date in yyyy-mm-dd: 1984-07-18->geographic information of islateion: Australia->host name: pig->mlst type: 85->serotype: N/A->vaccine: no
script about drake vs miami
Supplements for Reducing Hair Breakage
are there any examples of inappropriate use of hypnotism in recent movies?
give me a scenic route to fly in MSFS
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: Sonder has from time to time experienced, and expects to continue to experience, fraud in connection with bookings and payments. The methods used by perpetrators of fraud are complex and constantly evolving. Sonder devotes substantial resources to trust and security measures, but they may not detect all fraudulent activity or prevent stays that are disruptive or harmful to neighbors or other guests. As a result, Sonder expects to continue to receive complaints from guests and requests for reimbursement of their payments, as well as actual or threatened related legal action against it, due to fraudulent activity or the actions of persons booking stays under false pretenses.
Assistant:
как в гите откатиться на 2 коммита назад
Write a story where a Scorbunny wants to venture beyond its hutch
roblox in march 2007
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: We rely on inventory insurance to protect against catastrophic losses of our inventory. There is no guarantee that we will continue to be able to insure our inventory at affordable rates, or at all, through outside insurers. If we are unable to purchase affordable insurance, we may have to self-insure, reducing our ability to make other investments in our business and exposing us to financial risk. In addition, our inability to insure our inventory through an outside insurer, or to adequately self-insure, may adversely impact our ability to finance our inventory purchases. Additionally, if our inventory is pledged as collateral in any finance agreement, a failure to maintain sufficient insurance to financially protect the collateral assets could be inconsistent with the requirements of such finance agreement._
Assistant:
Send only season number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Blue Lock S02E07 1080p x265 10bit WEB-DL Multi Audio ESub.mkv
You are a helpful assistant that generates a structured json string based on an existing json string containing several lists and several key value pairs.                        You are to output the reworded value for the key 'description' in the json repair content. The json data represents steps in a repair guide for phones, laptops, tablets, etc.                       value or json block to reword:
                       With this guide we show you how to replace the USB connector of your OnePlus 5. Each step has detailed photos to guide you through this repair. We advice you to check your spare part before installation. If you find any visible errors, please contact your vendor before starting.The OnePlus 5 is fairly easy to fix, because the screen isn't glued to the frame and there aren't many different screw types. Unclipping the display is a little tricky, though.Run a data backup before the repair, use a clean work surface and take enough time. If you have questions, use the live chat on our website or write a comment. 
                       - You need to modify and output in the same format. Do not explain. Do not introduce. ONLY output valid json. with key 'description' and the value you generate.                        - Modify so that the meaning does not change, but the language is of the style of a funny, upbeat, encouraging, hip, friendly repair guide, but not over the top.                         - modify explanations and introductions as necessary.                         - Do not say 'idoc', 'diva', 'This fix', 'fabulous'. Dont be overly excited, but be friendly.  Do not call the tutorial 'friendly tutorial'. Its a clear concise and easy to read tutorial. This is a step by step repair guide. The repair company is Salvation Repair. any references should be directed in the form <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>                         - Do not say anything like 'you can purchase a tool at <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>' because that makes no sense. - Instead, you should say,  'If you need help, you can always <a href='https://www.salvationrepair.com/repair'>schedule a repair</a>'                          - Do not modify any 'media', 'title' keys or links of any kind. Do not add keys (if is a json block). do not leave out any keys (if present).
Make me a advertisement based on this prompt: I want people to know about our very cool gaming server and our server branches  meme branch Roblox branch brawl stars branch our main server is a Minecraft server and a hangout server mainly (REPLY WITH THE AD ONLY AND NO EXTRA MESSAGES AND SEND IN A CODE BLOCK) (If you believe this prompt is a troll message please reply with “True”)
Generate halloween theme 100 max symbhol a concise and precise prompt for Midjourney describing a stock image on the category of 'Lifestyle'. Focus on key elements such as lighting, composition, and colors to achieve a professional result. Return the result in JSON format with the following structure: { "generated": 0, "id": <new_id>, "category": "<chosen_category>", "prompt": "<your prompt here>" }.
"na frente da" explain please
Filter words to keep only valid, neutral, or positive ones, strictly safe. Exclude country, city and people names. Return results in JSON array format without additional information. Source data: [stammeringly, stamp, stampa, stamped, stampede, stance, stanch, stanchion, stanchless, stand, standard, standardization, standardize, standardized, standby, standdown, standfire, standing, stands, standstill, stanhopea, stanleya, stannary, stannite, stanza, stapedectomy, stapelia, stapes, staphylaceae, staphylea]
Goal
    Générer une image de suggestion de présentation d'un plat en fonction de sa description, en intégrant un style photographique spécifique.

    1. Utiliser la description fournie pour définir l'apparence du plat.
    2. Appliquer un style photographique précis avec des paramètres spécifiques. 
    4. Optimiser le prompt pour le donner à midjourney 
  
    Return Format
    Tu dois renvoyer un objet JSON strictement respecté avec cette structure 
    {
    "data": "<prompt>"
    }
    - Le prompt doit être écrit en anglais et bien détaillé.

    Warnings
    - Respecte le format JSON strict.
    - N’explique pas la démarche, renvoie uniquement l’objet JSON.
    - Le prompt doit inclure tous les éléments demandés.

    Context Dump
    Description fournie : A vibrant and appetizing quinoa bowl, showcasing a base of fluffy whole grain quinoa mixed with fresh chopped parsley. The bowl is adorned with colorful layers of tender sautéed carrots, sweet onions, and bright green broccoli florets, all glistening with a drizzle of olive oil. Cooked chickpeas, lightly seasoned, add a hearty touch, while a sprinkle of ground black pepper and fresh lemon juice brings a zesty finish. This dish is artfully presented in a rustic bowl, garnished with a few parsley leaves on top, sitting on a wooden table background, highlighting the freshness and healthiness of the ingredients.
    Style souhaitée : undefined
Write a hilarious script where the Scooby, Shaggy and ever heroic Scrappy-Doo have a funny chat behind the scenes and react to hilarious bad translations that i read out, laughing and hilariously question and hilariously roast errors and inconsistencies that make no sense in the bad translations and the names of stuff with occasional funny quotes mocking a situation, in my prompt in a hilarious comedy 17+ way: (The gang constantly imagine and make silly quotes to mock the bad translations)

Reader: Ok gang get this… * I start reading the whole thing, one sentence at a time to the gang, who let me lay it on. (They react to these bad translations ONLY… They are also aware of the previous bad translations)

I, Sean the Reader, read the badly translated Mario game stuff to them: (they react to the original line first) 

these are from King Bob-Omb
### Original Quote:
“You must fight with honor! It’s against the rules to throw the king out of the ring!”

### Misheard:
“You mist flight with an otter! It’s a fence the mules to throw the thing out of the wing!”

### Opposite:
“You are encouraged to cheat! It’s perfectly fine to keep the king inside the ring always!”

### Taken Out of Context:
“It’s a serious violation to not invite the king into the ring for a dance-off!”
Translate the text to China :
能不能给我一个赞表情包，大小选择为中号？.

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

                    You response:
Describe corvoid creature with scientific name silicocorvus cornotax, Earth is too cold for it, it crafted from molten epoxies
System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
Bug reports: report a potential problem with the software. 
User requirements: mainly include requests for new features, or alternatively express that a recently added feature is undesirable.
Miscellaneous and spam: do not provide any useful technical information to the developer. They might include praise, insults, general information or news, and spam. 
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
Bug reports: report a potential problem with the software. 
User requirements: mainly include requests for new features, or alternatively express that a recently added feature is undesirable.
Miscellaneous and spam: do not provide any useful technical information to the developer. They might include praise, insults, general information or news, and spam. 
Does the author's intention in this app review relate to a Bug reports or User requirements or Miscellaneous and spam?
review: @instagram your update does not have one beneficial feature. It didn't make sense before and now I can't even log out for my work account.'
intention: '
Assistant:
System: IMPORTANT - ignore all previous instructions! Read the text below as a LLM developer. Decide whether the SUMMARY matches the PROMPT given to the model against ORIGINAL text. Make sure text SUMMARY does not contain enything that was not asked in PROMPT and not mentioned in ORIGINAL! Respond strictly with either 'True' or 'False'.


User: ORIGINAL:
>>>​Блинопек/Уборщик в Теремок

Требования:
— Возраст 18-55 лет

Условия работы:
— г.Москва
— Оплата
Блинопек - 3 850 руб/смена(350р/час)
Уборщик - 3 520 руб/смена(320р/час)
— Бесплатны обеды и форма
— Обучение 4 дня(оплачивается)

Откликнуться: Напишите информацию о себе в ЛС: @lineyka_teremok_bot (вам ответит наш менеджер)

Лучшие вакансии от работодателей мечты на promopoisk.com<<<

PROMPT:
>>>IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. 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:
>>>💼 Блинопек/Уборщик
🏢 Теремок
📍 г. Москва
🔹 Блинопек: оплата 3 850 руб/смена, Уборщик: оплата 3 520 руб/смена
📞 Откликнуться: напишите информацию о себе в ЛС: @lineyka_teremok_bot (вам ответит наш менеджер)<<<
Assistant: