agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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:  Searching after the update Every time I search I get little or no results. I have performed the same searches before so I know results exist. Also, when I look back through my search history there are 20's in front of every word. Everything else works fine, but please fix!
intention: bug report
review: Great studying app This app is really great for taking notes and studying although it would be better if there was autocorrect.
intention: feature request
review:  Best app This app is more useful than any other i use
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:  Searching after the update Every time I search I get little or no results. I have performed the same searches before so I know results exist. Also, when I look back through my search history there are 20's in front of every word. Everything else works fine, but please fix!
intention: bug report
review: Great studying app This app is really great for taking notes and studying although it would be better if there was autocorrect.
intention: feature request
review:  Best app This app is more useful than any other i use
intention: other
Does the author's intention in this app review relate to a bug report or feature request or other?
review:  Faltu app :( Used it for 1 year then it lagging too much'
intention: '
Assistant:
What happens if the trial Invision Community expires? From what I understand the server is just a bunch of files and a mysql server?
Write an extremely long story about a man named Steven. Have everyone exclusively call the backrooms "The Halls". He was trapped in the backrooms for 5 years, and while he was there he met a friendly entity named Lost who quickly became like a brother to him. Lost was an 8 foot tall anthropomorphic dragon. Even though Steven escaped with various other survivors a month ago, Lost wasnt able to leave causing Steven severe depression and guilt. Lost was able to use his entity magic to give Steven beautiful dragon wings as a way to remember Lost. Steven now lives in an apartment complex with the rest of the escaped survivors. Have the story start with dialogue of his friend, a lesbian woman named Mal, checking up on him only to find him in his room depressed laying in his bed. She knows he hasnt handled losing his big brother well and she feels awful for him since Lost was the only family Steven ever had. She rubs Stevens wings, Steven shyly admitting it feels really nice. She asks him if he wants to fly and he refuses, saying he wanted to do that with his brother. She manages to get him to go to the lobby where all the other survivors are hanging out. He tries to hang out and talk with some friends until a survivor who always hated Steven mocks Stevens wings, calling Steven a furry. Steven angrily lashes out at the survivor before storming out. Have 5 mind bogglingly long chapters. Do not introduce the characters or settings. Have plenty of dialogue. Do not include graphic content.
Help me to rewite this code to Java, please
Top 20 piano players in history
Write an extremely long story about a man named Steven. He is a successful digital artist. Have the story start with Steven in his home office working on promotional art for a new anime that he was commissioned to make art for, jokingly asking himself why the main characters boobs are so massive before working on a background character who is directly based off of his boyfriend he convinced the company to let him add, when an anthropomorphic fox named Dusty playfully hugs him from behind and lovingly teases him and calls him a teasing pet name before casually asking if they want to watch some anime together. Steven immedietly hides the character. Steven still hasnt told Dusty about the easter egg and Dusty doesnt even know of the characters existence. The two have been gay lovers since middle school. Have various scenes of the two happily living together. Have a scene of Dusty seeing the character in the background while watching the first episode of the show and almost crying. Have a scene of dusty jokingly teasing Steven about how obvious it was from when they were just friends that Steven was super gay and listing the various Stereotypically gay things Steven did, Dusty mentioning how he caught Steven drawing a buff shirtless version of Dusty during study hall once. Do not introduce the setting or characters. Have 5 long chapters. Have plenty of dialogue.
The following is the Plackett-Burman experimental design matrix with experimental values of chitinase production by Paenibacillus Sabina strain JD2. Where X-1=Chitin , X-2=Glucose , X-3= Yeast Extract, , X-4=Peptone , X-5= (NH4)2SO4 , X-6= MgSO47H2O , X-7= CaCl2 and X-8= KH2PO4. Identify the most effective nutrients and give the rank.
I need your help to come up with a coherent 140-character title for my product. My set includes 40 digital backdrops related to poker such as poker falling cards, poker décor etc which can be used to place someone in this scene. Use some of the keywords from my list exactly as they are without changing them, but putting them into context. Do not just enumerate my keywords as that is not what I am looking for. My set includes 40 digital backdrops, ready to be downloaded and used for photo editing. Provide 15 versions of titles for this. Write in bold each time a keyword from the set is used. You must follow the format exacty as below Title: Number of Backdrops etc “. 
Example of title Format:  "The Land of Magic Mushroom Art: 40 Enchanted Landscape Fairytale Scene Digital Backdrops For Fairy Forest Photo Edit Digital JPG Files."

Keywords:
digital backdrop
photo backdrop
poker
photo booth props
las vegas
game night
gambling gifts
Custom Tapestry
Board game
jpg files
photo edit
instant download
digital background
say: “Strange. It wouldn’t suppose to be automatically used after purchasing a item”
Which officer positions must be filled for toastmasters club election
the following content is the metadata for a bacterial isolate from 3 different sources. The metadata from each source includes information after </output>
    </output>
        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
    <output/>

You must check if the metadata from 3 different sources are all consist. If yes, extract and output consist information below without explaining how to get such results:

    </output>
        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
    <output/>


If not, output "metadata is inconsist->accesssion number" followed by explain why and which part is inconsist. 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_947037165.1->species name: Erysipelothrix rhusiopathiae->strain name: 21S01201->isolate or collection date in yyyy-mm-dd: 2021 format->geographic information of islateion: Netherlands->host name: porpoise->mlst type: N/A->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_947037165.1->species name: Erysipelothrix rhusiopathiae->strain name: 21S01201->isolate or collection date in yyyy-mm-dd: 2021 format->geographic information of islateion: Netherlands->host name: Phocoena phocoena->mlst type: N/A->serotype: N/A->vaccine: no


source 2:
------------------------------
<output>
accession number: GCA_947037165.1->species name: Erysipelothrix rhusiopathiae->strain name: 21S01201->isolate or collection date in yyyy-mm-dd: 2021->geographic information of islateion: Netherlands->host name: porpoise->mlst type: N/A->serotype: N/A->vaccine: no
<output/>
Why might writing stories be your weakest point?
Write a current and up to date 2023 information of a constructive guide for my Scotland travel guide on “How to Get In Ben Nevis” with humanlike style, non repetitive phrases and avoidance of unnatural sentences and randomness while explaining in details. Please prevent writing listing/numbered format while generating the travel guide content.
I want to put together a week long comprehensive CrossFit program that provides strength training, calisthenics training, aerobics and ballistic plyometrics. Incorporate Olympic weightlifting and gymnastics. Use the rogue echo bike and concept2 rower
What's the advantage of Workspace OneDrive, with respect to Power BI
How to create a successful project in Algeria?
Tell me how to beat an internet addiction, in the form of an Elliott Smith song, and also a They Might Be Giant song
who will win the usl championship
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Example:
Question: What is your name?
Answer: My name is John.
Translation:
Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Teacher:In this task you are given a sentence. You must judge whether there exist two consecutive words within the sentence with flipped orders, that is, whether the sentence will make sense and be correct if the order of two consecutive words changes. Label the instances as "Inversion" or "Original" based on your judgment.
Teacher: Now, understand the problem? Solve this instance: The sun had only just gone down when they heard a rustle out in the darkness of the forest floor.
Student:
Answer: Original
catchy consulting business names
Thease are WordPress theme/plugin strings for i18nTranslate to Persian, please respect the official WordPress Persian glossary in your translations and give back pure text as I like copy/paste em.Here is the text to translate: Header
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: Our regulatory lending limit as of December 31, 2022, to any one customer or related group of customers was $124.4 million for unsecured loans and $207.4 million for secured loans. Our lending limit is substantially smaller than that of many financial institutions with which we compete. While we believe that our lending limit is sufficient for our targeted market of small to mid-size businesses within the four specialty lending operations upon which we focus as well as affinity group members, it may in the future affect our ability to attract or maintain customers or to compete with other financial institutions. Moreover, to the extent that we incur losses and do not obtain additional capital, our lending limit, which depends upon the amount of our capital, will decrease._
Assistant:
Create a code for snake game
battery low notification in android studio java full code
I am writing to confirm whether you have received my final transcript. Please find attached. If yes, please verify it and clear my offer condition.Besides, I wonder wether I am satisfy with the entrance award. 

Waiting for your early reply. 

Besides, my study permit application is still processing. Is there anything I should pay attention to, like payment deadlines, course selection deadlines, that kind of thing. thank you
How Can I use the infinite pessoal of Portuguese?
%sql
select
  seller.payload__seller_code seller_seller_code,
  
  seller.payload__trade_name seller_trade_name,
  act.payload__terminal_brand AS terminal_brand,
  act.payload__terminal_model AS terminal_model,
  act.payload__serial_number serial_number,
  act.payload__terminal_code terminal_code,
    act.payload__situation__status terminal_status,
  act.payload__token__code token_code,
  act.payload__token__situation__status token_status,
 from_unixtime( (act.payload__token__situation__status_update_date__date) / 1000, "yyyy-MM-dd HH:mm:ss") token_update,
  act.payload__connectivity connectivity,
  act.payload__equipment_type equipment_type,
from_unixtime( (act.payload__created_at__date) / 1000, "yyyy-MM-dd HH:mm:ss") created_at,
from_unixtime( (act.payload__activated_date__date) / 1000, "yyyy-MM-dd HH:mm:ss") activated_date,
from_unixtime( (act.payload__deactivated_date__date) / 1000, "yyyy-MM-dd HH:mm:ss") deactivated_date,
from_unixtime( (act.payload__updated_at__date) / 1000, "yyyy-MM-dd HH:mm:ss") updated_at,
from_unixtime( (act.payload__updated_at__date) / 1000, "yyyy-MM-dd HH:mm:ss") last_config
from delta.`/pnms/stage/event/payment_channel/terminal_activation_ms/terminal/current` act
  left join delta.`/pnms/stage/event/onboarding/seller_ms/seller/current/` seller 
    on seller.country = act.country
    and seller.tenant = act.tenant
    and seller.payload__seller_code = act.payload__seller_code
  left join delta.`/pnms/stage/event/payment_channel/terminal_journey_ms/terminal_code/current` j
    ON act.country = j.country
    and act.tenant = j.tenant
    and act.payload__terminal_code = j.payload__terminal_code
  left JOIN DELTA.`/pnms/stage/event/onboarding/merchant_ms/merchant/current` AS merchant 
    ON merchant.payload__merchant_id = seller.payload__merchant_id
    AND merchant.COUNTRY = seller.COUNTRY
    AND merchant.TENANT = seller.TENANT    
where 1=1
and j.country IN ("AR")
  
  and j.payload__seller__seller_code in  ("0000059366")
--and act.payload__terminal_code in ("CL000121")
--and act.payload__serial_number in ("NAA900795214")
one chapter story script; about a british female in full name, wearing sky team gb cycling skinsuit in her bedroom after-or-before riding bicycle, shrink down suddenly to microscopic size with suit still weared on; next chapter.
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:

هاني شنو عشاكم عاد إنتوما قلي
I've done this wsl --mount \\.\PHYSICALDRIVE1 --partition 1 how to cd into it
write a 1994 nba season with john starks worst shooting
For each concept, add detailed information on the following cinematic aspects that will make it better and needed :
 
1. Visual Style (e.g., gritty, vibrant), 
2. Camera Angle (e.g., close-up, wide shot), 
3. Lighting (e.g., soft, dramatic), 
4. Color Palette (e.g., warm tones, monochrome), 
5. Effects (e.g., slow motion, lens flare), and 
6. Composition Elements (e.g., rule of thirds, leading lines). 

Be specific and make sure the descriptions match the tone and genre of the text. 

Text to enhance: 
Sure! Here’s a detailed critique of the provided text, focusing on logic, creativity, clarity, and overall quality, along with actionable suggestions for improvement:

### Logic
**Critique:** The prompt effectively sets up a scenario that aligns with the themes of cosmic and alien horror. However, the description of the alien entity could benefit from more logical consistency regarding its interaction with the astronaut.

**Improvement Suggestion:** Clarify how the alien entity affects the astronaut. For instance, instead of saying the tendrils "seem to seep into the astronaut's suit," you could specify that they are actively distorting the suit or causing visible damage. This would create a more coherent image of the alien's influence and enhance the sense of danger.

### Creativity
**Critique:** The concept of an eldritch alien entity is a classic trope in cosmic horror, and while the imagery is strong, it could push the boundaries of creativity further.

**Improvement Suggestion:** Introduce a unique element to the alien entity that sets it apart from typical portrayals. For example, you could describe the entity as having a sound or a whisper that is felt rather than heard, creating an unsettling auditory experience that complements the visual horror. This would add a layer of creativity and depth to the alien's presence.

### Clarity
**Critique:** The prompt is generally clear, but some phrases could be streamlined for better readability. The repetition of certain phrases (e.g., "based on the user idea of an Alien Horror movie") can be distracting.

**Improvement Suggestion:** Remove redundant phrases and simplify sentences for clarity. For example, instead of starting with "Based on the user idea of an Alien Horror movie," you could begin with "Inspired by the concept of Alien Horror, I created a detailed prompt for a text-to-image LLM model." This would make the introduction more concise and engaging.

### Overall Quality
**Critique:** The overall quality of the prompt is strong, but it could benefit from a more cohesive structure that guides the reader through the imagery and themes.

**Improvement Suggestion:** Organize the prompt into distinct sections with headings (e.g., "Concept," "Visual Elements," "Atmosphere," "Technical Requirements"). This would help the reader navigate the text more easily and understand the different aspects of the movie cover being described. Additionally, consider adding a brief conclusion that encapsulates the essence of the horror being portrayed, reinforcing the emotional impact of the image.

By
script about kroger brand arnold palmer
학회 초록인데  영어교정 부탁해.Background
Single dose intratracheal bleomycin (BLM) has been used for the study of fibrotic lung disease including IPF, but it fails to recapitulate the features of usual interstitial pneumonia(UIP). We aimed to developed a repetitive BLM model that results in lung fibrosis with characteristics of human disease in the aged mice.
Methods
Mice over 22 weeks ages were given intratracheal BLM every 2wk until 4 months and lungs were harvested. Lungs were evaluated for fibrosis severity, collagen contents, senescence markers, TUNEL assays and extracellular matrix components.
Results
Lungs from repetitive BLM mice had marked fibrosis with prominent alveolar epithelial cell (AEC) hyperplasia and cystic dilatation of bronchioles, similar to UIP. Compared with single dosing, repetitive BLM mice had more fibrosis by morphometry, scoring and collagen contents. In addition, increased apoptotic AECs and reduced inflammatory cells were found by repetitive BLM treatment. Compared with young mice, p-Rb, senescent marker was significantly increased by repetitive dose in aged mice. 
Conclusions.
We established that repetitive intratracheal BLM model in aged mice results in marked lung fibrosis with AEC hyperplasia and honeycombing change, similar to features of UIP.
what is the best way to check if the current prediction matches any of the previous predictions without taking too much memory  in image detection problem using python?