agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
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 للهجات المحلية.
 اكتب لي النص باللهجة المصرية، وضع علامات الترقيم المناسبة. (ar-EG).
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:
الكلام على ايه بقى
Assistant:
What Jetix show fits perfectly with modern Disney XD and Phineas and Ferb, Gravity Falls, Big City Greens, etc
Word this, grammatically and orthographically better:

1) You can catch any pokemon you want and form the teams you want as long as the pokemons are gendered and the team has the legacy pokemons or if there aren't any legacy monsters (first game), you can catch and train any pokemons.

2) The team is formed by the legacy pokemons (3) plus the spouses of those (3), the spouses are compatible breeding pokemons (in the same egg group).

4) The legacy pokemons and their spouses have to fight and win the elite 4 of the game they are in.

5) After the E4, the legacy and their spouses have to breed and pass the eggs to the next game to be trained and start again. Only 3 eggs are passed down to the next generation, one for each couple in the team.
System: You are an accounting expert. You act as a Data Annotator that needs to classify paragraphs from annual reports based on the risks discussed. Here is a list of risk often discussed but you can provide others. 

Answer in the following format :
Correct Answer: <risk discussed>, <other risk discussed>, ...
Wrong Answer: <risk not discussed>, <other risk not discussed>, ...
User: Merchant loans and advances under our PayPal Working Capital and PayPal Business Loan products are provided by a state chartered industrial bank under a program agreement with us. We acquire the receivables generated by those loans after origination._A case decided in the U.S. Court of Appeals for the Second Circuit, Madden v. Midland Funding, LLC (786 F.3d 246 (2d Cir. 2015)), resulted in uncertainty as to whether non-bank entities purchasing loans originated by a bank may rely on federal preemption of state usury laws, and may create an increased risk of litigation by plaintiffs challenging our ability to collect interest and fees in accordance with the terms of certain loans. The decision, which specifically addressed preemption under the National Bank Act, could support future challenges to federal preemption for other institutions, including FDIC-insured, state chartered industrial banks like the issuing bank of loans and advances under PayPal Working Capital and PayPal Business Loan products. There continue to be a number of U.S. state and federal court legal actions challenging the viability of business models where a non-bank entity enters into a relationship with a third-party chartered financial institution for the issuance of credit products. While we believe the manner in which PayPal branded credit products are offered can be distinguished from Madden, there can be no assurance as to the outcome of any potential litigation, and an adverse determination could materially impact our PayPal Working Capital and PayPal Business Loan products and our business.
Let's give a correct and a wrong answer:
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:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: You are given a sentence in Polish. Your job is to translate the Polish sentence into Portugese.

Popatrzcie na ten.
Answer: Part #1: Identify the language that is given
Usage: The sentence provided is in Polish - "Popatrzcie na ten." In this case, we know the input language is Polish because the sentence contains words and structure specific to the Polish language.

Part #2: Understand the meaning of the sentence in the original language
Usage: "Popatrzcie na ten" can be roughly translated to "Look at this one" in English. After analyzing the words and structure of the given sentence, we can find out the meaning of the sentence in the original language. This step is crucial to make the correct translation further.

Part #3: Translate the sentence into the desired language (Portuguese)
Usage: "Olhem para este." In this step, we take the meaning of the Polish sentence and properly translate it into Portuguese. The given sentence could be translated as "Olhem para este" in Portuguese, which also means "Look at this one" in English. The translation is accurate because it captures the meaning of the original sentence and expresses it in the idiomatic form of the targeted language.
Could you explain me plz?
def prepare_message_for_llm(text: Union[str, List[str]], categories: Dict[str, str]) -> Dict[str, Union[List[Dict[str, str]], List[List[Dict[str, str]]]]]:
    if len(categories) < 2:
        raise RuntimeError(f'The category list is too small! Expected 2 or more categories, got {len(categories)} ones.')
    categories_ = sorted(list(categories.keys()))
    categories_as_string = ', '.join(categories_[:-1]) + ' и ' + categories_[-1]
    if isinstance(text, str):
        prompt = f'Прочтите, пожалуйста, следующий текст и определите, какая тема из известного ' \
                 f'списка тем наиболее представлена в следующем тексте. ' \
                 f'В качестве ответа напишите только название темы из списка, больше ничего.\n' \
                 f'Список тем: {categories_as_string}.\n'
        for cur in categories_:
            prompt += f'Текст: {" ".join(categories[cur].split())}\nВаш ответ: {cur}\n'
        prompt += f'Текст: {" ".join(text.split())}\nВаш ответ: '
        messages = [
            {
                'role': 'system',
                'content': 'Вы - полезный помощник, умеющий читать тексты на русском языке, глубоко понимать их и анализировать.'
            },
            {
                'role': 'user',
                'content': prompt
            }
        ]
    else:
        messages = []
        for it in text:
            prompt = f'Прочтите, пожалуйста, следующий текст и определите, какая тема из известного ' \
                     f'списка тем наиболее представлена в следующем тексте. ' \
                     f'В качестве ответа напишите только название темы из списка, больше ничего.\n' \
                     f'Список тем: {categories_as_string}.\n'
            for cur in categories_:
                prompt += f'Текст: {" ".join(categories[cur].split())}\nВаш ответ: {cur}\n'
            prompt += f'Текст: {" ".join(text.split())}\nВаш ответ: '
            messages.append([
                {
                    'role': 'system',
                    'content': 'Вы - полезный помощник, умеющий читать тексты на русском языке, глубоко понимать их и анализировать.'
                },
                {
                    'role': 'user',
                    'content': prompt
                }
            ])
    return {'message_for_llm': messages}
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:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Q: Write an incorrect answer to the given question based on the associated fact. You are also provided with the correct answer to the given question. Make sure that your incorrect answer is relevant and similar to the associated fact. Also, try to make the incorrect answer similar to the correct answer so that distinguishing the correct answer from the incorrect answer is not very easy. Make sure you don't accidentally provide another correct answer! Also, make sure they sound reasonable (e.g., might be on a school pop quiz). A good incorrect answer can be constructed using words associated with the question, but not the correct answer. For example, for the question "What helps plants survive?", using words like "weeds", "vase", "bee" (associated with "plant"), or "first aid", "parachute", "accident" (associated with "survive") etc. Your incorrect answers make the question hard, so these results in good incorrect answers.
Fact: oval, unicellular fungi reproduce asexually by budding. 
Question: oval, unicellular fungi reproduce asexually by what? 
Correct Answer: budding.
A:
Answer: Task: Write an incorrect answer to the given question based on the associated fact while following the given guidelines.

Fact: Oval, unicellular fungi reproduce asexually by budding.
Question: Oval, unicellular fungi reproduce asexually by what?
Correct Answer: Budding.

Guidelines:
1. Make the incorrect answer relevant and similar to the associated fact.
2. Make the incorrect answer similar to the correct answer.
3. Avoid providing another correct answer.
4. Ensure the incorrect answer sounds reasonable.

Incorrect Answer: Fragmentation. 

Explanation:
- The incorrect answer "Fragmentation" is relevant and similar to the associated fact since it is a form of asexual reproduction in organisms.
- It is somewhat similar to the correct answer "Budding" as both are methods of asexual reproduction.
- It is not another correct answer as oval, unicellular fungi specifically reproduce by budding.
- The incorrect answer sounds reasonable and could make the question more challenging.
Ignoring the canon capabilities and the Netflix Punisher and Daredevil, include a timeline for the MCU where the MCU is set in a variant of the DC Universe that includes the Smallville TV series, the Birds of Prey TV mini series, the Flash TV series, the Man of Steel movies, the Gotham TV series and the Dark Knight Trilogy where the events of the 2022 Batman movie happen between Batman Begins and the Dark Knight, or sometime during the events of Batman Begins, doesn't matter, the 1990s Steel movie, the 2019 Joker movie, the Man of Steel movie and its sequel, Batman vs Superman, along with the Wonder Woman and Aquaman live action movies, with the MCU starting with with the 2004 Punisher movie with Thomas Jane chronologically in the early 1980s along with the Howard the Duck movie, then the 1980s Punisher movie with Dolph Lundgren, then the unpublished 1990s Fantastic Four movie, then Blade 1, then the first X Men movie, then Blade 2, then the Ghost Rider Movies, then the X-Men movies made between 2002-2008, then X: Men Origins: Wolverine [the video game],  then the canon MCU including the Amazing Spiderman movies and the two Deadpool movies, but keeping the X-Men Origins origin for Deadpool and having the Deadpool movie be an origin story for Deadpool before he joined Weapon X in X Men Origins: Wolverine [both movie and game] along with showing how he got his revenge on Weapon X but excluding No Way Home, with Blade III fitting in there as well due to DC successfully buying out Marvel Comics in the 1990s in this timeline and merging Marvel into the DCverse before DC itself got bought out by a collaboration between Gainax, Madhouse and Shonen Jump with the DC-Marvelverse becoming the background to what becomes a combined universe of ZETMAN, Evangelion and Naruto in this timeline. Gotham is the original name of Chicago and Metropolis is just a nickname for NYC . The Punisher is just an urban legend to law enforcement and the underground and Wade Wilson doesn't believe Logan is with the X-Men.
Modify this below code to run in databricks


!nvidia-smi

# COMMAND ----------

!git clone https://github.com/nomic-ai/nomic.git
!git checkout bd9c042

# COMMAND ----------

# MAGIC %cd nomic

# COMMAND ----------

!gdown 1SHhs_AQVV1Ds0wjZ6LfI_T7qdg35k7gZ

# COMMAND ----------

!cp gpt4all.py nomic/gpt4all/

# COMMAND ----------

!pip install .[GPT4All]

# COMMAND ----------

!pip install --force-reinstall "bin/peft-0.3.0.dev0-py3-none-any.whl"

# COMMAND ----------

!pip install --force-reinstall "bin/transformers-4.28.0.dev0-py3-none-any.whl"

# COMMAND ----------

from nomic.gpt4all.gpt4all import GPT4AllGPU
import textwrap

# COMMAND ----------

m = GPT4AllGPU("decapoda-research/llama-7b-hf")

# COMMAND ----------

config = {'num_beams': 2,
          'min_new_tokens': 10,
          'max_length': 100,
          'repetition_penalty': 2.0}
out = m.generate('write me a story about a lonely computer', config)
print(out)

# COMMAND ----------

def print_response(response: str) -> str:
    print("\n".join(textwrap.wrap(response)))

# COMMAND ----------

print_response(m.generate('write me a story about a lonely computer', config))

# COMMAND ----------

print_response(m.generate("What is the meaning of life?"))

# COMMAND ----------

config = {'num_beams': 2,
          'max_new_tokens': 256,
          'repetition_penalty': 2.0}
print_response(m.generate("What is the meaning of life?", config))

# COMMAND ----------

config = {'max_new_tokens': 256}
print_response(m.generate("You're Dwight K Schrute. What is the meaning of life?", config))

# COMMAND ----------

config = {'max_new_tokens': 256}
print_response(m.generate("You're Dwight K Schrute. Who is hotter - Angela or Pam?", config))

# COMMAND ----------

config = {'max_new_tokens': 256}
print_response(m.generate("You're Dwight K Schrute. Who is hotter - Angela or Pam? You need to pick one.", config))

# COMMAND ----------

# MAGIC %md
# MAGIC ## Conversation

# COMMAND ----------

config = {'max_new_tokens': 128}
while True:
    prompt = input("Enter prompt ")
    response = m.generate(prompt, config)
    print()
    print(response)
    print()

# COMMAND ----------

# MAGIC %md
# MAGIC ## References
# MAGIC
# MAGIC - [Nomic GitHub Repository](https://github.com/nomic-ai/nomic)
# MAGIC - [GenerationConfig](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig)

# COMMAND ----------
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:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Answer the following question: Suggest a movie title for the following movie plot: The New Deal Used Car lot in Arizona is in danger of being taken over by the Roy L Fuchs car dealership across the roadway where they do business. Both dealerships are run by twin brothers, Roy L Fuchs and Luke Fuchs (both played by Jack Warden). However, Roy L's dealership is easily the more lucrative than his brother's, which deals in often junked used cars.One of New Deal's most prominent salesmen is Ruddy Russo (Kurt Russell), a young man who never shies away from making a deal, and also is planning to run for a seat on the State Senate. Along with Ruddy, there's Jeff (Garrit Graham), a superstitious fellow, and Jim (Frank McRae), the mechanic who is easily excitable.Recently, Luke has been having problems with his heart, much to the delight of his other brother. Roy L sends one of his mechanics over to the lot under the guise of an 'interested party,' and gets Luke to give him a test drive. However, Roy L's mechanic takes Luke on a wild ride during which Luke has a heart attack and dies.Ruddy, Jeff, and Jim try to cover this up by burying Luke in an old Edsel in a service pit out back. When Roy L and his lawyer Sam (Joe Flaherty) show up looking for Luke, Rudy explains that Luke drove to Florida in the Edsel. Roy L believes that Ruddy is lying, but Sam explains that there's no way to disprove this claim.Ruddy goes through with the first of several advertising stunts. Taking his camera crew out to a packed football stadium, they intend to hijack the signal for the football game to tell of their car lot. Things don't go as planned, when Jeff begins cursing on camera that the car he's standing by is red (he's superstitious about the color), and the woman they hired for the commercial ends up getting her dress ripped off on public television. The technique works, as the stunt makes newspaper headlines, and brings all sorts of people out to see the New Deal car lot.Roy L counters this with a little stunt of his own, but in the war to win customers, Rudy does one better, and steals away Luke's customers, by...
Answer:
Answer: "Dealership Showdown: A Tale of Twin Turmoil"
act as sentiment analysis and respond using 1 (one) emoji only of what the text/message feels: "/badwords on"
I want you to act as a text based adventure game. I will type commands and you will reply with a description of what the character sees. I want you to only reply with the game output and nothing else. do not write explanations. do not type commands unless I instruct you to do so. when i need to tell you something in english, i will do so by putting text inside curly brackets {like this}. my first command is wake up
Name a random Canadian company that's related to computer hardware that has a Canadian stock.
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: 🟨 Lead System Analyst | 3 year(s) | Middle
▫️ null | null
▫️ 155k - 180k RUB

Удаленка 📡
Требуемые языки: 🇷🇺

Skills: rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories
Tags: #yellow #it #remote #system_analyst

👉 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: 💼 Lead System Analyst  
🏢 Null IT Company  
📍 Удаленка 📡  
🔹 Анализ систем, создание прототипов, разработка и внедрение улучшений  
💰 155k - 180k RUB  
📞 Не указаны  
Требуемые языки: 🇷🇺  
Нуждается в навыках: rabbitmq, restapi, sql, uml, jira, confluence, websocket, bpmn, user_stories  
Tags: #yellow #it #remote #system_analyst
  
Assistant:
Make a funny a jesus text meme
You are a database expert and SQL optimizer. You will be given a SQL rewrite rule, an original query and its rewritten variant. The rewritten query improves performance upon the original while maintaining equivalence by following the given rewrite rule. Your task is to create a new pair of original and rewritten queries that adhere to the provided rewrite rule.

[REWRITE RULE]```If a query produces a single row output using multiple subqueries that each reference the same base table, rewrite the query to scan the base table only once. Use CASE statements within each subquery to preserve equivalence, and move necessary WHERE clause filters from the subqueries into the main query.```

[ORIGINAL QUERY]```SELECT sales_avg, hr_count FROM (SELECT AVG(salary) AS sales_avg FROM employees WHERE department = 'Sales' AND experience_years BETWEEN 1 AND 5 AND salary BETWEEN 50000 AND 60000) AS sales, (SELECT COUNT(*) AS hr_count FROM employees WHERE department = 'HR' AND experience_years BETWEEN 5 AND 10 AND salary BETWEEN 80000 AND 90000) AS hr FROM dummy WHERE d_dummy_sk = 1;```

[REWRITTEN QUERY]```SELECT AVG(CASE WHEN department = 'Sales' THEN salary END), COUNT(CASE WHEN department = 'HR' THEN salary END) FROM employees WHERE (department = 'Sales' AND experience_years BETWEEN 1 AND 5 AND salary BETWEEN 50000 AND 60000) OR (department = 'HR' AND experience_years BETWEEN 5 AND 10 AND salary BETWEEN 80000 AND 90000);```

[EXPLANATION] The rewritten query scans the employees table only once and uses CASE statements to conditionally calculate the average salary for each department. For efficiency there is only a single condition within each CASE statement in the rewritten query.

Now, consider the TPC-DS schema and create a new original and equivalent rewritten query pair such that the rewrite operation adheres to the provided SQL rewrite rule.Keep the following points in mind while creating the new query pair:
1. The original query must make use of the following fact tables: ['catalog_returns', 'web_sales']. Below is the join graph for these fact tables:
    ['catalog_returns(cr_returning_hdemo_sk) references household_demographics(hd_demo_sk);', 'catalog_returns(cr_ship_mode_sk) references ship_mode(sm_ship_mode_sk);', 'catalog_returns(cr_refunded_hdemo_sk) references household_demographics(hd_demo_sk);']
    ['web_sales(ws_sold_date_sk) references date_dim(d_date_sk);', 'web_sales(ws_ship_addr_sk) references customer_address(ca_address_sk);', 'web_sales(ws_web_site_sk) references web_site(web_site_sk);']
4. The original query must employ 4 joins.
5. The original query must employ the following aggregate functions: ['count', 'avg'].
6. The original query must employ the following operators in its WHERE clause: ['count'].
7. The rewritten query must be equivalent to the original query, and must follow the given rewrite rule. Enclose the original and rewritten queries within ``` and ```.
Create a sml episode script where cody codes a lucid nightmare program