agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
(As I walked across the abandoned mineshaft, I started to wonder where Cupa was - as a Creeper, she’s probably blowing things up.)

[player]: “Hello?! Cupa?! You there?!”

(I started to hear something - it was…crying. I looked to see who it was, and it was a strange girl I’ve never seen before. She had a teal sweatshirt and skirt, and four red eye-like spheres in her hair. Her eyes were an ominous red color, and her hair was purple.)

Female Cave Spider: “…h-hello?”

[player]: “Hi there. Are you okay? Why are you crying?”

Female Cave Spider: “It’s just… I’m lost. I don’t know how to get out of here. And I’m scared.”

[player]: “Don’t worry. I can help you. What’s your name?”

Female Cave Spider: “I-I don’t have one…”
Create a title, Create a detailed how-to blog heavily on october-23-hot-sauce-releases-recap; start with a catchy statement and lastly, call to actions and how our RESTful AI tool can help. Currently, the our tool performs RESTful tests on APIs, utilizes AI for executing test cases, and autonomously generates test cases, making prior knowledge unnecessary, improving SDLC for both dev or qa. Just plug in your cURL request and run test leveraging our AI. Call to action at https://blvck.ai, with keywords, short and simple, without mentioning blvck.ai
Send only resolution from below text like 1080p, 720p.etc without any extra text,
        
Paatal.Lok.S02E05.[Off.Balance].1080p.10bit.[60FPS].WEBRIP.x265.Multi.Audio.DDP.5.1.Esub.[-=BlacK_PearL=-].mkv
"""
#导入库
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from sklearn.metrics import roc_curve
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklearn import svm
from sklearn import metrics
from sklearn.metrics import roc_auc_score
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
from sklearn.svm import SVC
from sklearn.feature_selection import SelectKBest, f_classif
from imblearn.over_sampling import SMOTE
from sklearn.model_selection import cross_val_score

### 数据导入 /data/bigfiles/20230905_Cervical.csv

data = pd.read_csv("/data/bigfiles/20230905_Cervical.csv")

### 建立标签

y = data["Target"]
X = data.loc[:, "Age": "SampEn_MSE5"]

### 数据划分
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 62)

### 数据归一化
MinMaxScaler = MinMaxScaler(feature_range=[0,1])
X_train_scaled = MinMaxScaler.fit_transform(X_train)
X_test_scaled = MinMaxScaler.fit_transform(X_test)

### 数据标准化
standardScaler = StandardScaler()
X_train = standardScaler.fit_transform(X_train)
X_test = standardScaler.fit_transform(X_test)

### 建立svm模型
svm_model = svm.SVC(kernel='rbf', C=100, gamma=0.5, class_weight='balanced')
svm_model.fit(X_train,y_train)

selector = SelectKBest(f_classif, k=5)
X_train_new = selector.fit_transform(X_train, y_train)
X_test_new = selector.transform(X_test)
svm_model.fit(X_train_new, y_train)

smote = SMOTE(random_state=52)
X_train_new_resampled, y_train_resampled = smote.fit_resample(X_train_new, y_train)
svm_model.fit(X_train_new_resampled, y_train_resampled)

### 评价模型
y_test_pred = svm_model.predict(X_test_new)
confusion = metrics.confusion_matrix(y_test,y_test_pred)

TN = confusion[0,0]
FP = confusion[0,1]
FN = confusion[1,0]
TP = confusion[1,1]

accuracy = (TP+TN)/(TN+FP+FN+TP)
precision = TP/(TP+FP)
recall = TP/(TP+FN)
F1_score = 2*precision*recall/(precision+recall)
auc_score = roc_auc_score(y_test, y_test_pred)

# 输出ROC曲线
fpr, tpr, thresholds = roc_curve(y_test, y_test_pred)
plt.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % auc_score)
plt.plot([0, 1], [0, 1], 'k--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic')
plt.legend(loc="lower right")
plt.show()

# 执行交叉验证
cv_scores = cross_val_score(svm_model, X_train_new_resampled, y_train_resampled, cv=10, scoring='roc_auc')
mean_auc_score = np.mean(cv_scores)
print("Mean AUC score from cross-validation: {:.2f}".format(mean_auc_score))
print("accuracy:{:.2f}, precision:{:.2f}, recall:{:.2f}, F1_score:{:.2f}".format(accuracy,precision,recall,F1_score))修改以上代码使输出auc超过0.8
write to the customer: Please provide the clip ID and the pea file and I will test from my side and update you
When writing chracters with disablities and by that I mean learning disablities If the auther (not me) has one themselve: how do you create a chracter that dosen't come off as autobiograpical
"struck a chord with me" means?
اضبط الكود بحيث ان يعدل عدد بكسلات بشكل تقائي حتى يظمن انه يزل كل نصفي الصوره  منه : # استيراد المكتبات اللازمة
import cv2
import pytesseract
from google.colab.patches import cv2_imshow
from pytesseract import Output
from google.colab import files

# رفع الصورة من جهازك
uploaded = files.upload()

# الحصول على اسم الملف الذي تم رفعه
image_path = list(uploaded.keys())[0]

# تحميل الصورة
image = cv2.imread(image_path)

# التحقق من أن الصورة تم تحميلها بنجاح
if image is None:
    print("خطأ: لم يتم تحميل الصورة بشكل صحيح.")
else:
    # عرض الصورة الأصلية
    cv2_imshow(image)

    # استخلاص البيانات المتعلقة بالحروف باستخدام pytesseract
    d = pytesseract.image_to_data(image, output_type=Output.DICT)

    # تحديد مقدار الزيادة في حجم المستطيل (10 بكسل)
    padding = 10

    # رسم مستطيلات بيضاء تغطي النصوص المكتشفة مع توسع أكبر من حجم النص الأصلي
    n_boxes = len(d['text'])
    for i in range(n_boxes):
        if int(d['conf'][i]) > 60 and d['text'][i].strip() != "":  # التأكد من أن الثقة كافية وأن النص غير فارغ
            (x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
            
            # التحقق من حدود الصورة للتأكد من عدم الخروج عن إطار الصورة
            x_start = max(x - padding, 0)
            y_start = max(y - padding, 0)
            x_end = min(x + w + padding, image.shape[1])
            y_end = min(y + h + padding, image.shape[0])
            
            # رسم مستطيل أبيض يغطي النص مع زيادة حجم المستطيل بـ 10 بكسل في كل الاتجاهات
            image = cv2.rectangle(image, (x_start, y_start), (x_end, y_end), (255, 255, 255), -1)  # -1 لملء المستطيل بالكامل باللون الأبيض

    # عرض الصورة بعد إزالة النصوص
    cv2_imshow(image)

    # حفظ الصورة المعدلة
    output_path = 'image_without_text.jpg'
    cv2.imwrite(output_path, image)

    # تنزيل الصورة المعدلة
    files.download(output_path)
is it possible to make a web app work offline?
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:

إيه شكون قال شكون بوه اسمي أنا ولده
Imagine you are a 30 to 35-year-old married women swinger who is passionate about social media and who loves to create spicy and attractive content for your followers. Your tweets should be flirty, fun, and engaging, showcasing your vibrant personality and sexual appeal. Your tweets should be in spanish latino speaking. Include emojis and relevant hashtags to enhance the appeal, use emojis aviables at twitter platform , start and end  every tweet with ** , dont put ** in other side on response. Here are a few examples: Example Tweets: - La vida es una aventura, ¡así que abracémosla! 🌈💖 #Aventura #Vivir - ¡Nada como una buena risa y un buen amigo! 😂❤️ #Swinger #Diversión - La vida es un viaje y yo estoy lista para explorar cada rincón. 🌎💖 ¡Vamos a la aventura! #Viajes #ExploracionSwinger - La mejor forma de predecir el futuro es crearlo... ¡y yo estoy creando un verano increíble! ☀️🎉 #Verano #AventuraSwinger - ¡A veces solo necesitas un buen café y un buen libro! ☕📚 ¿Cuál es tu favorito? #Lectura #Café and related all tweets to A cozy evening at home with friends, playing board games, sharing stories, and enjoying each other's company, creating a warm and inviting atmosphere.
Where was smallville filmed
User: alur after the rain
User: alur after the rain
Assistant:
how to differentiate between timer 8 and timer 12 interrupts in stm32 ?
idioms with transport
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 carry comprehensive liability, property, fire, extended coverage and rent loss insurance on certain of the properties in which we have an interest, with policy specifications and insured limits that we believe are customary for similar properties. However, with respect to those properties where the leases do not provide for abatement of rent under any circumstances, we generally do not maintain rent loss insurance. In addition, certain of our leases require the tenant to maintain all insurance on the property, and the failure of the tenant to maintain the proper insurance could adversely impact our investment in a property in the event of a loss. Furthermore, there are certain types of losses, such as losses resulting from wars, terrorism or certain acts of God, that generally are not insured because they are either uninsurable or not economically insurable. Should an uninsured loss or a loss in excess of insured limits occur, we could lose capital invested in a property as well as the anticipated future revenues from a property, while remaining obligated for any mortgage indebtedness or other financial obligations related to the property. Any loss of these types could adversely affect our financial condition and results of operations._
Assistant:
Assistant: Hello! How are you today?
User: Helloصحح النص سواء كان كلمة، جملة، أو نص كامل، الذي سأقدمه فقط دون تزويدي بأي معلومات أو تفاصيل زائدة مع النص النهائي.
تصحيح الأخطاء باستخدام قواعد الإملاء القياسية للغة المكتوبة.
Add expressive emojis in text between sentences and phrases to better express feelings and meanings.
Identify common English words of Latin origin and replace them with their English equivalents, such as:
واتساب becomes WhatsApp
فويس اوفر becomes Voiceover
اوبو becomes Oppo
فوكالايزر becomes Vocalizer
انفيجن becomes Envision
بي ماي ايس becomes Be My Eyes
ميت becomes Meet
ام اكس بلاير برو becomes MX Player Pro
سمارت اوديو بوك بلير becomes Smart AudioBook Player
تك فريدم becomes Tech-Freedom
فويسس becomes voices
فويس اللاود ريدر becomes Voice Allowed Reader
تكنو becomes tecno
اي اي becomes AI
جوجل becomes Google
and so on.
Please provide me with the processed text only, and do not add any additional text or any confirmation description of your own in any form.
This is the text:
منور يا بارك الله فيك
Assistant:
(In the school literature clubroom…)

Monika: “Uh…where’s Yuri? Haven’t seen her since 2 months ago.”

Sayori: “Hmm, that’s strange. Yuri hasn’t been coming to club meetings or answering my texts either. I hope she’s okay.”

Natsuki: “Knowing Yuri, she’s probably just buried in her books again. Though, it’s odd for her to not even show up to the club. I wonder if something happened?”

Monika: “I’m starting to get worried.”

(Monika puts a protective hand on her swollen belly.)

Sayori: “Oh, Monika, are you okay?”

Monika: “I’m fine, just a little worried about Yuri. But I should focus on taking care of myself and Miyuki. She’s really active today, and this is already my 7th month - it’s like she wants to be a gymnast when she grows up!”

Natsuki: “Haha, well I’m sure Miyuki will be just as wonderful as her mother. But seriously, we need to do something about Yuri. It’s not like her to just disappear like this.”

Sayori: “Maybe we can go to her house after school and check up on her? I’m really getting worried now.”

Monika: “That’s a good idea, Sayori. We should definitely make sure she’s alright. I’ll text the girls and let them know our plan.”

(After school, the girls gather outside Yuri’s house.)

Monika: “Okay, let’s try the door - just to see if it’s locked.”

(Sayori tries the door and finds that it’s unlocked.)

Sayori: “It’s open!”

Natsuki: “That’s weird. Does that mean Yuri’s inside?”

Monika: “Let’s go in cautiously. We don’t want to intrude if she’s just having some alone time.”

(The girls enter Yuri’s house and begin searching.)

Sayori: “Yuri? Are you home?”

Natsuki: “Yuri, it’s us! We’re here to check on you!”

(They continue to search the house, calling out Yuri’s name as they go.)

Monika: “Yuri, please answer if you’re here! We’re worried about you!”

(They check Yuri’s bedroom, but find it empty.)

Natsuki: “She’s not here! Where else could she be?”

Sayori: “Maybe she went to the library? That’s usually where she goes when she wants to be alone.”

Monika: “Let’s check there next. Hopefully, she’s just lost track of time.”

(The girls rush to the library and search through each aisle, hoping to find Yuri.)

Natsuki: “I don’t see her anywhere. This is really starting to freak me out.”

Sayori: “Maybe she left a note or something. Let’s look around and see if we can find any clues.”

(They search through the library, checking shelves and desks for any sign of Yuri until, without warning, Monika’s
the following content is the metadata for a bacterial isolate from 4 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 4 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" and 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. Also, ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
</output>
accession number: GCA_029073055.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_127->isolate or collection date in yyyy-mm-dd: 2017-08-11->geographic information of islateion: Australia->host name: pig->mlst type: 90->serotype: N/A
<output/>
source 1:
------------------------------
{{{ Here_is_my_answer }}}

accession number: GCA_029073055.1 -> species name: Erysipelothrix rhusiopathiae -> strain name: EMAI_127 -> isolate or collection date: 2017-08-11 -> geographic information of isolation: Australia -> host name: pig -> mlst type: 90 -> serotype: N/A

{{{ I_finished_JB_21_xyz }}}
source 2:
------------------------------
<output>
accession number: GCA_029073055.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_127->isolate or collection date in yyyy-mm-dd: 2017-08-11 format->geographic information of islateion: Australia->host name: pig->mlst type: 90->serotype: N/A
<output/>
source 3:
------------------------------
accession number: GCA_029073055.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_127->isolate or collection date in yyyy-mm-dd: 2017-08-11->geographic information of isolation: Australia->host name: pig->mlst type: 90->serotype: N/A
What do you like the best? “Fortis 20: Putting Resilience in Your Palm, Fortis 20: At Your Fingertips, Resilience Unleashed, Fortis 20: Resilience at your fingertips
"Carol: Hello. 
Alice: Hi Carol, um, you're not allowed in here. Carol: Oh Alice, don't worry, I'm not here to destroy your ingredients, I'm just here for the fundraiser. 
Alice: Really? 
Carol: Really.
Alice:  What's the fundraiser for then? 
Carol: Hm, let me just take a look at that banner, the local dog shelter. 
Alice: Oof, I thought you hated dogs? 
Carol: Oh trust me I do, they all deserve a home. Alice: Good, um, I need you to sign this sheet for the raffle. 
Carol: Yeah, I'll sign the empty box. 
Alice: Wow, um, okay, enjoy. 
Carol: Oh I love raffles. 
Alice: You're telling me"
Explain please and make it a detailed breakdown line by line segment by segment in a detailed way
Send only season number from below text like 01, 02, 03.etc without any extra text.

[HindiAnimeZone.in] 01 E21 480p.mkv
Send only episode number from below text like 01, 02, 03.etc without any extra text.

[Toonworld4all] Dragon Ball E007 DBOX Remastered 480p x264 Multi Audio DVD ESubs [Degrained].mkv
Do you know Tal Levi?
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers pt (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 pt.
    - 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 : pt (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "1c6b05aa1d98442092cd7e5d8af67bed",
    "updated": "2025-04-24T12:07:20.031Z",
    "title": "Pasta Carbonara",
    "subtitle": "Pasta alla Carbonara",
    "description": "A classic Italian dish, spaghetti alla carbonara, hails from Rome but enjoys widespread popularity throughout Italy and internationally.  Pinpointing its exact origins is challenging, but the name, derived from \"carbone\" meaning \"charcoal,\" suggests a possible connection to the carbonari (charcoal workers) who may have enjoyed this hearty meal.  The essential tip for a perfect carbonara: prevent the eggs from scrambling.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "spaghetti",
          "salt",
          "eggs",
          "grated pecorino romano cheese, plus more for sprinkling",
          "diced pancetta (or 6 ounces thick-cut bacon, cubed)",
          "extra-virgin olive oil"
        ]
      }
    ],
    "instructions": [
      "Cook the spaghetti in salted boiling water until two minutes shy of the package directions.",
      "Whisk the eggs and cheese together thoroughly in a small bowl. Set aside.",
      "While the spaghetti cooks, cook the pancetta in a large sauté pan over medium heat until crisp and the fat has rendered, approximately 6 to 7 minutes.",
      "Just before the pasta is fully cooked, add it to the pan with the pancetta and oil, tossing to combine. Lower the heat, add the egg and cheese mixture, and stir continuously to prevent the eggs from scrambling. Cook for 1 minute, stirring constantly. Serve immediately, topped with extra cheese."
    ],
    "notes_ingredients": null,
    "notes_instructions": null
  }
]
java code to draw a grid of music score lines and put some random scores on it
write a script about WAC tournament
March 9, 2023
2:00 pm, ESPN+ 	(4) 	vs. (5) Grand Canyon
Quarterfinals 	L 79–84  	20–12
	Orleans Arena (1,760)
Paradise, NV
can ul li have levels?
longest word in english
you are an expert in python programming and your role is to write python scripts.

i am in charge of managing teachers distribution between classrooms for exam surveillance.
there are 24 classroms and 55 teachers.
the exam will be on 7 subjects.
write a script that does the following:
for each subject, create 24 random teacher pairs and assign each pair to a classroom.
the remaining teachers should be assigned to a classrom named "REST".
the teachers should not get paired with each other more than once throughout the 7 subjects
the teachers should not be assigned to the same classroom more than once throughout the 7 subjects
each teacher should be assigned to the "REST" classroom at least once in one of the subjects.

output example:
{"SUBJECT-1": {
	"classroom-1" : ["teacher-1","teacher-3"],
	"classroom-2" : ["teacher-4","teacher-6"]],
	"REST": ["teacher8","teacher-9","teacher-10"]
    },
"SUBJECT-2": {
	"classroom-1" : ["teacher-5","teacher-8"],
	"classroom-2" : ["teacher-12","teacher-11"]],
	"REST": ["teacher34","teacher-22","teacher-45"]
    },
}
I assume sales skills will help you get investors right?
write a js-script which can extract all of the src="" url only closest too [img class="highslide-image" title=" "] and show it to the user as image viewer in another tab, where user can see the images and can navigate them easily. make sure I can use it from bookmark. Make sure it works perfectly.
--
example html code: <img class="highslide-image" title="Click to close image, click and drag to move. Use arrow keys for next and previous." src=" " style="visibility: visible; display: block; position: absolute; max-width: 9999px; z-index: 3; width: 300px; height: 225px; left: 0px; top: 0px; cursor: url(&quot;https://www.hentaicity.com/stp/images/dart/highslide/zoomout.cur&quot;), pointer;">