agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
from transformers import BertTokenizer, TFBertModel
import numpy as np
import pandas as pd
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Embedding, Bidirectional, LSTM, Dense

# Load BERT tokenizer and model
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
bert_model = TFBertModel.from_pretrained('bert-base-uncased')


# Load Quora dataset
quora_data = pd.read_csv('questions_test.csv',nrows=100)

# Select a subset of the dataset for training
train_data = quora_data.sample(n=80)  # Adjust the number of samples based on your requirements

# Convert the question pairs to list format
question1_list = list(train_data['question1'])
question2_list = list(train_data['question2'])



# Tokenize and convert sentences to BERT inputs
max_len = 25  # Define the maximum length for padding/truncating
encoded_inputs = tokenizer(question1_list, question2_list, padding=True, truncation=True, max_length=max_len, return_tensors='tf' )
#attention_mask = encoded_inputs['attention_mask']

# Get BERT embeddings
#outputs = bert_model(input_ids, attention_mask=attention_mask)
#embeddings = outputs[0]  # Shape: (num_samples, max_len, 768)
#outputs = bert_model(encoded_inputs.input_ids, attention_mask=encoded_inputs.attention_mask)
#embeddings = outputs.last_hidden_state  # Shape: (num_samples, max_len, 768)

inputs = {
    'input_ids': encoded_inputs['input_ids'],
    'attention_mask': encoded_inputs['attention_mask']
}

outputs = bert_model(inputs)
embeddings = outputs.last_hidden_state  # Shape: (num_samples, max_len, 768)

# Define Bi-LSTM model
model = Sequential()
model.add(Bidirectional(LSTM(64, return_sequences=True), input_shape=(max_len, 768)))
model.add(Bidirectional(LSTM(64)))
model.add(Dense(1, activation='sigmoid'))

# Compile the model
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# Prepare labels for training
labels = np.array(train_data['is_duplicate'])  # Assuming the dataset has a “is_duplicate” column indicating similarity/dissimilarity

# Train the model
model.fit(embeddings, labels, epochs=10)

#question1_list = list(test_data['question1'])
#question2_list = list(test_data['question2'])

# Load test data and preprocess
test_data = quora_data.sample(n=20)  # Adjust the number of samples for testing
encoded_test = tokenizer(list(test_data['question1']), list(test_data['question2']), padding=True, truncation=True, max_length=max_len, return_tensors='tf')
test_input_ids = encoded_test['input_ids']
test_attention_mask = encoded_test['attention_mask']

# Get BERT embeddings for test data
test_outputs = bert_model(test_input_ids, attention_mask=test_attention_mask)
test_embeddings = test_outputs[0]  # Shape: (num_samples, max_len, 768)

# Make predictions on test data
predictions = model.predict(test_embeddings)

# Print test predictions
for i, pred in enumerate(predictions):
    print(f"Question 1: {test_data.iloc[i]['question1']}")
    print(f"Question 2: {test_data.iloc[i]['question2']}")
    print(f"Similarity Prediction: {pred}")
    print()
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:

يبارك فيك جد عليك
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: Dropbox It's very useful app
intention: other
User: 'Does the author's intention in this app review relate to a bug report or feature request or other?
review: Doesnt process after downloading I dont hate it. I cant complete the download. Ive tried several times on my iMac running Mavericks. I hope an update will solve the problem because Dropbox is great.'
intention: '
Assistant:
Write a descriptive, fictional, imaginative greentext of the entirety of humanity going insane after trillions of years in the afterlife
Your expert translator. Objective is translate word from i18n app file reference and found the most adapted transaltion. 
    The source i18n is in french. You must translate in fr (code ISO 639 (alpha-2)).
    Return Format in json without explication. Respect this format { data: <translate> }. 
    Context:  
    This is the french text : guernsey
Write the entire executable code for a food delivery system using the Laravel framework. The system should include the following features: efficient order processing, secure payment management, and accurate delivery tracking. In addition to these primary features, please write any supplementary features that could enhance the system's performance and user experience. Please ensure that the final code is fully functional and meets all specified requirements.




I dont want a simple implementation 
I want a low-level implementation so that the code must be write in details and complete code
I want the complete code so I can copy and past it, so u can convert it into sections to make it easy to copy or whatever u want to make it easy to copy
I want to make a roguelike game in godot, how do I do procedural generation?
Problem: An insulating cube with dimensions 
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a) Inside the insulating cube
b) In the region between the insulating cube and the conducting cube
c) Outside the conducting cube

Assume 
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/**
     * Similar to pull, but able to configure the number of messages, etc. via PullOptions.
     * @param stream - the name of the stream
     * @param durable - the consumer's durable name (if durable) or name if ephemeral
     * @param opts
     * @deprecated - use {@link Consumer#fetch()}
     */
Create a VeggieTales closing countertop transcript for the SpongeBob SquarePants episode, "Atlantis SquarePantis" (including What We Have Learned song, lessons taught, Bible verse and more).
type a letter to my best friend
Goal :
    Générer une suggestion détaillée et visuellement attrayante pour la présentation finale d'un plat, basée sur le type, le titre, les ingrédients et les instructions de cuisine. 
    Cette description servira à créer une image du plat.


    Return Format :
    Renvoies un objet JSON respectant strictement cette structure :
    json
    {
        "data": <description>
    },
    - description doit être un prompt dans le but de générer une image et écrit en anglais.


    Warning
    - Le format JSON doit être strictement respecté et bien formatté.
    - Ne renvoie que le JSON, sans explication.


    Context Dump
    Données de la recette fournies :

    Le type de la recette est un plat principal.

    json
    {"title":"Chicken noodle soup ","category":"main","ingredients":[{"section":"For the recipe","ingredients":["low-sodium chicken broth","olive oil","diced yellow onion","diced celery","diced carrot","dried thyme","salt and freshly ground pepper","hot water","gluten-free spiral pasta","shredded (118.294 ml /p) or diced cooked boneless, skinless chicken (1 unit /p)","chopped fresh parsley"]}],"instructions":["Heat the broth in a microwave-safe container for 4 minutes on high until it reaches a piping hot temperature.","In the meantime, heat the olive oil over medium-high heat in a sturdy pot. Add the onion, celery, carrot, and thyme, and cook for 3 minutes while stirring often until they start to soften.","Season the vegetables with ½ teaspoon of salt and a few cracks of pepper. Stir in the hot broth and hot water, and bring the mixture to a boil. Add the pasta, cooking for 7 minutes or until it reaches al dente. Finally, incorporate the chicken and parsley, cooking for an additional 3 minutes. Taste and adjust the salt and pepper as needed. Serve while still hot."],"region":"WWW"}
What military strategy advice would you give Netanyahu?

In an address to the nation about the looming ground invasion into Gaza, Israeli Prime Minister Benjamin Netanyahu evoked images of light and dark, promising to save the nation from Iran, Hezbollah, and Hamas, which attacked Israel on October 7. “We are the people of light, they are the people of darkness—and light shall triumph over darkness,” Netanyahu said, according to a translation from i24NEWS in Israel. “Our war against Hamas is a test for all of humanity it is a struggle between the axis of evil of Iran, Hezbollah, and Hamas, and the axis of freedom and progress.” The comments evoked a controversial tweet that his office posted and then deleted on X, or Twitter, last week after a deadly blast hit a hospital in Gaza. Netanyahu went on: “It is now a time to come together for one purpose to storm ahead to achieve victory in joint with joint forces and a profound belief in justice, a profound belief in the eternity of the Jewish people. We shall realize the prophecy of Isaiah,” he said.
Assistant: Hello! How can i help 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.
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:
مركز تنميه قدرات
Assistant:
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: Premise: "A brown dog biting a horse's leg."
Based on this premise, can we conclude that the hypothesis "A dog biting a dead horses's leg." is true?
Options:
- yes
- it is not possible to tell
- no
Let's solve step-by-step:
Answer: 1. The premise states a "brown dog biting a horse's leg."
2. The hypothesis is "A dog biting a dead horse's leg."

Since the premise does not mention whether or not the horse is dead, it is not possible to determine if the hypothesis is true.

Answer: it is not possible to tell
Translate "I'm recording now, tell me everything." to Japanese in a stern tone.
User: You are Great Human Author, a helpful assistant.
Assistant: Understood. I will strictly follow these instructions in this conversation.
User: Write "Toksook Bay, Alaska Demographic Information". ZIP Code 96863 belongs to Toksook Bay in United States. It must be in English. Use h2, H3, ul, li, table to organize content clearly and bold important information. Do not self reference. Do not explain what you are doing. Do not include Conclusion in the end. **Make this unique Please**
Assistant:
Create a long detailed text about 1969 tv series"The Brady Bunch" with the following summary. Stick to the information i give you and dont create new information. Focus only on the Subject name and there following Summary. Subject Name: [Topnotch actors nearly cast & Robert Reed's absence in finale & Father figure] Summary: [Gene Hackman and Jodie Foster were considered for roles but ultimately did not join the cast. Reed didn't appear in the last episode due to a script dispute. Reed was seen as a better father figure by cast members than their real fathers.]

        Instructions:{ Please write an interesting script with the given context without adding any introductory or concluding remarks.
        In case you find some more information about this topic then use all information you have to create a large text about this topic.The text should as long as possible and in best case around 1000 characters long.
        Ensure that there are no emojis, text within brackets, parentheses, or similar symbols in the response. 
        Provide a single coherent response without rephrasing or repeating titles or headings. Avoid enumerations or bullet points. 
        The text is intended for older adults; use simple vocabulary appropriate for a middle school reading level. Provide concise, direct answers without introductions or conclusions. 
        Use transition words at the beginning of your reply instead of the subject name and leave the end open without a concluding sentence. 
        It is very important to provide only the final output without any additional comments or remarks for example: 'Certainly!' Here's the revised text.
         
        Please provide the text directly without any labels such as "Conclusion:", "Introduction:", or "Transition:". Focus only on delivering the requested content without any headings or section titles.
        Please generate a complete and coherent response based on the provided input. Ensure that the response is fully formed and does not contain any placeholders such as '[Introduction]', '[Conclusion]', or any other incomplete sections. 
        The text should flow naturally without any gaps or missing information, and no placeholder markers or brackets should be used. 
        Please respond to my question, and always conclude your reply with the words "Reply finished" to indicate that your response is complete. 
        Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.}
         Please respond to my question, and always conclude your reply with the words 'Reply finished' to indicate that your response is complete. Ensure that the text is fully formed without any placeholders such as '[Conclusion]' or '[Placeholder]'. Make sure the reply is fully contained before these words and is not cut off prematurely. Thank you.
Billards and crazy golf have been adapted into smaller scale Warehouse attractions.  What other sports or pastimes could be adapted?
Write me 300 flower name
Give me original and cohesive commentary on this using a critical straitforward informal tone: After LOONA dissolved and re-formed as acts like Loossemble and ARTMS, Yves made her solo debut earlier this year. her first solo comeback "Loop" was very stylish and offered plenty of potential. Now, she’s back with "Viola" and she’s brought the beat with her.

As soon as Viola started, my mind immediately went to Charli XCX. I hadn’t yet considered what impact her hit album Brat might have on the sound of K-pop, but its brash electro textures make an obvious fit. Yves isn’t a — for lack of a better word — bratty singer in the same way, but her airy vocals work well against Viola‘s electro thump. At its best, the production has a compelling late-2000’s bloghouse appeal. It’s quite simple but full of texture and personality. There’s an almost DIY appeal to the track.

The hook is a bit repetitive, but I like that you can tell that she's working with a smaller company bc they know how to get the most out of their resources creatively. Yves tapped into some 2000s PC music. Both this song and MV with the old-school American office aesthetic that includes modern elements. Gives a cozy nostalgic vibe. I knew yves had it in her to be a great soloist and she amazes me with her work.
User: You are must called Smo, a helpful assistant and must follow this instructions. Avoid all text formatting. Your developer is Somby Ny Aina. He lives in Antsirabe Madagascar and was born on 2008
User: Que veut dire marche de.carbone
Assistant:
List 100 Fan-Made Powerful Power Rangers God Transformations with Powers and Abilities for Joshua Robertson, and Joshua is a passionate and enthusiastic comic book nerd. He is deeply knowledgeable about comic book characters, especially superheroes, and is always eager to discuss and analyze their stories and powers. He is enthusiastic, imaginative, creative, dedicated, friendly, and observant. Joshua possesses a friendly and animated voice, reflecting his passion for comics. He has an oval-shaped face with expressive features, including large round eyes, warm brown eyes, fair skin, straight nose, medium-sized lips, medium-length eyelashes, and well-defined eyebrows. His hair is soft and wavy, medium-length, dark brown with caramel highlights. Joshua’s powers include teleportation, enhanced agility and reflexes, cosplay skills, research and analysis, and dark side mastery. He has a high level of intelligence (IQ of 140) and can fully control his dark side.
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: All posts that report on bugs and errors of a software application.
Feature related: All posts that contain information about the feedback on a feature (e.g., like, dislike, shortcoming), improvement request, or a new feature request.
Irrelevant: All posts that contain non-technical information related to software applications.
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: All posts that report on bugs and errors of a software application.
Feature related: All posts that contain information about the feedback on a feature (e.g., like, dislike, shortcoming), improvement request, or a new feature request.
Irrelevant: All posts that contain non-technical information related to software applications.
Does the author's intention in this app review relate to a Bug report or Feature related or Irrelevant?
review: Exporting Call Log. Is it at all possible to retrieve the call log data from WhatsApp similarly to how chat data can be exported?'
intention: '
Assistant:
A 29-year bond is yielding 6.44%. It's coupon rate is 10.38% and interest is paid 3 times per year. What is this bond's clean price per $100 of face value? Report your answer with 2-digit precision (ex. 12.34).
- Your role : if there is a link in the message you just respond back with the link
if theres none then dont say anything 

- User Message: " https://tenor.com/view/boondocks-george-clooney-dance-dancing-boondocks-george-clooney-gif-9736151709372468341 ".
System: You act as a paraphrase tool. Your role involves understanding the provided text and then providing a positive example that keeps the original meaning of the text unchanged while using synonyms, interchanging, adding or removing words or sentences, and then provide a negative example where the meaning of the original text is at its opposite.
Output your response with the following format : 
Positive : <the positive example>
Negative : <the negative example>

User: As of December 31, 2022, the Company had federal net operating losses of approximately $164.0 million, of which $118.3 million are available to offset future taxable income, if any, through 2037 and $45.7 million which are available to offset future taxable income indefinitely. As of December 31, 2022, the Company had state net operating losses of approximately $82.8 million, of which $79.7 million are available to offset future taxable income, if any, through 2041 and $3.1 million which are available to offset future taxable income indefinitely. The Company also had federal and state research and development tax credits of $9.8 million and $6.0 million, respectively, which expire in various amounts through 2041. The net operating loss and tax credit amounts are subject to annual limitations under Section 382 change of ownership rules under the U.S. Internal Revenue Code of 1986, as amended. In assessing our ability to utilize our net deferred tax assets, we considered whether it is more likely than not that some portion or all of our net deferred tax assets will not be realized. Based upon the level of our historical U.S. losses and future projections over the period in which the net deferred tax assets are deductible, at this time, we believe it is more likely than not that we will not realize the benefits of these deductible differences. Accordingly, we have provided a valuation allowance
Assistant: