DataHammer/scimrc huggingface dataset:
Question: Describe how you planned a father and son high school senior trip
Answer: My son and I, embarked on a biking trip from San Francisco to LA right before my son's college applications and essays were due. To start our journey, we rented a truck and transported our bikes from LA to San Francisco. We returned the truck in San Francisco and started our journet on our bikes. Our trip took eight days and was full of adventure and unexpected twists and turns. We had to stay in motels and camp sites along the way and endure biking many uphill miles. Our meals tasted the best after a lenghty daily travel, and the most enjoyable was the deep conversations we had without interruption of phone or social media. I shared my never spoken before youth experiences growing up in Iran. He seemed delighted to be hearing my experience and taking a mental note every step of the way.
Upon reflecting on our trip, we encountered numerous challenges. We lost our way for several miles, and to compound our predicament, our bikes broke down along the way. In addition, we were cited by the police for riding our bikes on the freeway and physically assaulted. Despite all these setbacks, we pushed ourselves to ride up to 80 miles each day.
Even to this day, my son frequently recalls our trip and how it brought us closer together. He also acknowledges the spiritual growth that we experienced as a result of the journey.
He was accpeted as the only two students to Berkely and many months later I asked him what set him apart from all A's students which he then responded my colledge essay and our SF biking trip.
Question: Given the introduction of ChatGPT, tell me how many releases there are since the fist launch and when they were launched.
Evidence: ChatGPT was launched as a prototype on November 30, 2022. It garnered attention for its detailed responses and articulate answers across many domains of knowledge. Its uneven factual accuracy, however, has been identified as a significant drawback. Following the release of ChatGPT, OpenAI's valuation was estimated at US$29 billion in 2023.

The original release of ChatGPT was based on GPT-3.5. A version based on GPT-4, the newest OpenAI model, was released on March 14, 2023, and is available for paid subscribers on a limited basis.
Answer: There are two ChatGPT versions so far. The first release was on Nov 23rd, 2022, and the second launch was released on Mar 14th, 2023.
Question: Why USA is best ?
Answer: Because USA is powerful and give respect and Wealth and health benefits to all of their citizen
Question: Identify which instrument is string or percussion: Tifa, Pipa
Answer: Pipa is string, Tifa is percussion.
Question: what are coolest things to do in Amsterdam
Answer: Amsterdam is one of the most popular european city for tourists. Amsterdam offers variety of museums , great restaurants , canal rides , casinos and plenty of options to do party at nice pubs, bars.

One of the most popular museum is Van Gogh and Rijks museum. Van Gogh museum is popular amongst art lovers and Rijks museum is popular amongst history, travel and artefacts lovers 

There are plenty of bars , pubs and nice restaurants to enjoy night life while admiring great views of Amsterdam canals dipped in the evening lights
Question: Are large language models actually smart like humans?
Answer: Large language models (LLMs) can give the appearance that they are very human like in our interactions with them.  This is because they can respond to our answers the way a human would respond.  Large language models under the hood are very good at pattern recognition.  They are training on vasts amounts of data from the internet and have billions of machine learning parameters that can be tuned.  These models can even be customized or trained on a set of data that is industry specific to be able to provide industry specific answers to industry specific questions.  They work by taking the user prompt and converting it into a pattern, and then it looks across all the different patterns the LLM has been trained on and when it finds a match it returns it to the end user.  It is important to note that large language models at this moment are not humans, do not exhibit human behavior, and are incapable of feeling human emotion and making decisions based on this.
Question: What results does the human evaluation show?
Evidence: In this section we present results of our experiments, first in the original dataset without any source degradation (Section SECREF18 ) and then in the setup with various source degradation strategies (Section SECREF25 ).
Table 3 shows the human evaluation results. They are consistent with the automatic evaluation results when it comes to the preference of humans towards the deliberation-based setups, but show a more positive outlook regarding the addition of visual information (del+obj over del) for French.
Answer: They are consistent with the automatic evaluation results when it comes to the preference of humans towards the deliberation-based setups, but show a more positive outlook regarding the addition of visual information (del+obj over del) for French.
Question: Give me three ideas for a fun dinner party
Answer: Here are some engaging party ideas that put food at the center!
- Tapas party: make lots of small dishes, such as stuffed mushrooms, that are easily passed and snacked on throughout an evening. This is great for a casual get together of friends, and leaves plenty of time for socializing. 

- Potluck: ask all attendees to bring one dish. This is a great way to let your guests showcase their own skills and share something they love, while also reducing the amount of prep required by the host!

- One-dish meals: if you don't want to spend all day prepping, make a fun dish such as paella (large Spanish rice dish) or chili (green or red) that you can prepare in one large serving. These can also be made to accommodate dietary restrictions, such as vegetarian or gluten-free guests.
Question: List in a comma-separated list the members of the band Muse.
Evidence: Muse are an English rock band from Teignmouth, Devon, formed in 1994. The band consists of Matt Bellamy (lead vocals, guitar, keyboards), Chris Wolstenholme (bass guitar, backing vocals), and Dominic Howard (drums).
Answer: Matt Bellamy (lead vocals, guitar, keyboards), Chris Wolstenholme (bass guitar, backing vocals), and Dominic Howard (drums).
Question: Identify which instrument is string or woodwind: Catalan shawm, Tres
Answer: Tres is string, Catalan shawm is woodwind.
Question: How well establish is the Cuban red-tailed hawk as a species?
Evidence: The Cuban red-tailed hawk (Buteo jamaicensis solitudinus) is a subspecies of red-tailed hawk native to the Bahamas, Florida, and Cuba.

Like other island races, the validity of this subspecies has been called into question, but it has its defenders as well. Generally, this subspecies appears as a diminutive version of B. j. umbrinus in plumage characteristics but is considerably isolated from that race.
Answer: The validity of this subspecies has been called into question, but it has its defenders as well.
Question: Why is the D silent in words like Bridge?
Answer: The letter "J" was created by an Italian in 1524, initially as an alternative to the roman numeral I.  Its usage as a typical alphabet letter in English became common in the 17th century.  Before this addition, to make the sound J in English, we used the letters "dg."  You can typically tell how old a word is by whether it uses the "dg" or J in its spelling; the newer words use the letter J.
Question: When will George R.R. Martin release the sixth book in the series "A Song of Ice and Fire"?
Answer: No release date has been announced yet for the sixth book titled "The Winds of Winter." Author George R.R. Martin previously indicated on various occasions that it would be released in 2016, then 2017, then 2018. In October 2022, he appeared on "The Late Show with Stephen Colbert" and said that approximately three-quarters of the novel had been written.
Question: Give me a list of six different types of flowers I could buy someone
Answer: Carnations, Roses, Tulips, Peonies, Daffodils, Lilies
Question: List the 6 naturally occurring noble gases.
Evidence: The noble gases (historically also the inert gases; sometimes referred to as aerogens) make up a class of chemical elements with similar properties; under standard conditions, they are all odorless, colorless, monatomic gases with very low chemical reactivity. The six naturally occurring noble gases are helium (He), neon (Ne), argon (Ar), krypton (Kr), xenon (Xe), and the radioactive radon (Rn).
Oganesson (Og) is a synthetically produced highly radioactive element. Although IUPAC has used the term "noble gas" interchangeably with "group 18" and thus included oganesson, it may not be significantly chemically noble and is predicted to break the trend and be reactive due to relativistic effects. Because of the extremely short 0.7 ms half-life of its only known isotope, its chemistry has not yet been investigated.
For the first six periods of the periodic table, the noble gases are exactly the members of group 18. Noble gases are typically highly unreactive except when under particular extreme conditions. The inertness of noble gases makes them very suitable in applications where reactions are not wanted. For example, argon is used in incandescent lamps to prevent the hot tungsten filament from oxidizing; also, helium is used in breathing gas by deep-sea divers to prevent oxygen, nitrogen and carbon dioxide toxicity.
The properties of the noble gases can be well explained by modern theories of atomic structure: Their outer shell of valence electrons is considered to be "full", giving them little tendency to participate in chemical reactions, and it has been possible to prepare only a few hundred noble gas compounds. The melting and boiling points for a given noble gas are close together, differing by less than 10 °C (18 °F); that is, they are liquids over only a small temperature range.
Neon, argon, krypton, and xenon are obtained from air in an air separation unit using the methods of liquefaction of gases and fractional distillation. Helium is sourced from natural gas fields that have high concentrations of helium in the natural gas, using cryogenic gas separation techniques, and radon is usually isolated from the radioactive decay of dissolved radium, thorium, or uranium compounds. Noble gases have several important applications in industries such as lighting, welding, and space exploration. A helium-oxygen breathing gas is often used by deep-sea divers at depths of seawater over 55 m (180 ft). After the risks caused by the flammability of hydrogen became apparent in the Hindenburg disaster, it was replaced with helium in blimps and balloons.
Answer: The six naturally occurring noble gases are:
1. Helium (He)
2. Neon (Ne)
3. Argon (Ar)
4. Krypton (Kr) 
5. Xenon (Xe)
6. Radon (Rn)
Question: Is this hockey, baseball, or both?
Answer: Puck, Ball, Ice, Dirt, Skates, Cleats, Gloves, Glove, Bat, Stick, Pads, Helmet
Question: What methods are the most effective approaches in abstracting latent representations from a paragraph?
Evidence: Abstracting latent representations from a long sequence of words, such as a paragraph, is a challenging task. While several novel neural network models BIBREF25 , BIBREF26 have been introduced in recent years for encoding a paragraph, Recurrent Neural Network (RNN)-based methods remain the most effective approaches. RNNs, especially the long-short term memory (LSTM) BIBREF27 models, have been widely used to encode a paragraph for machine translation BIBREF28 , dialogue systems BIBREF29 and text summarization BIBREF30 because of its ability in modeling long-distance dependencies between words. In addition, among four typical pooling methods (sum, mean, last and max) for calculating sentence representations from RNN-encoded hidden states for individual words, max-pooling along with bidirectional LSTM (Bi-LSTM) BIBREF31 yields the current best universal sentence representation method BIBREF32 . We adopted a similar neural network architecture for paragraph encoding.
Abstracting latent representations from a long sequence of words, such as a paragraph, is a challenging task. While several novel neural network models (Zhang et al., 2017b,a) have been introduced in recent years for encoding a paragraph, Recurrent Neural Network (RNN)-based methods remain the most effective approaches.
Answer: Recurrent Neural Network (RNN)-based methods.
Question: What's the best genre of music?
Answer: It depends on who you ask. Some people will claim that a primary genre of music — rock, jazz, pop, etc. — should top the list, but there are hundreds of categories of music and musical tastes and preferences vary by person.
Question: Given this paragraph, what is the out of state acceptance rate at the University of Virginia?
Evidence: For the undergraduate Class of 2023, the University of Virginia received a record 40,815 applications, admitting 24 percent. Approximately 40 percent of those admitted are non-white. Matriculated students come from all 50 states and 147 foreign countries. UVA is required, by Virginia state law, to matriculate two-thirds of its undergraduate student body from its pool of in-state applicants. As a result, its acceptance rate for in-state students (36 percent) is nearly twice the out-of-state rate (19 percent) as of 2019. The university has seen steady increases to its applicant pool in recent decades, and the number of applications has more than doubled since the Class of 2008 received 15,094 applications. As of 2014, 93 percent of admitted applicants ranked in the top 10 percent of their high school classes.
Answer: The out of state acceptance rate at the University of Virginia is 19%.
Question: Which movie do you like the most and why do you like it?
Answer: The movie that I like the most is Matrix. I like it from both cinematic and subject point of view. Cinematically, it was a great movie in its time. It had great special effects and computer graphics (CG) was used extensively in it. The creators even introduced new ideas in filming the scenes like using multiple cameras at different angles to create some of the mind-blowing action scenes. The cast also did a great job. I've watched some behind the scenes and noticed how much effort all of them had put to create the best and believable scenes. 
But the most interesting part of the Matrix movie for me is its subject. It is about a virtual world created and controlled by computers which simulates the life and creates the illusionary perception for the humans that they are really living, but in fact it is only their minds that are the habitants of this world and their real bodies are imprisoned in incubators and are being utilized at energy sources by the computers. I really like the idea and also how one can generalize it to the real world that we are living in. What if this world and the life on it is just a projection or a shadow of a higher form of life, like a two-dimensional shadow of a three-dimensional object in space.
Question: Do archaeologists dig up dinosaurs?
Answer: No, archaeologists do not dig up dinosaurs. They study human culture; therefore, they dig sites relating to human occupation.
Question: What automatic metrics are used for this task?
Evidence: For automatically evaluating our methods, we propose to use widely used metric for image/video captioning. This is because the proposed CommonGen task can be regarded as also a caption task where the context are incomplete scenes with given concept-sets. Therefore, we choose BLEU-3/4 BIBREF28, ROUGE-2/L BIBREF29, CIDEr BIBREF30, and SPICE BIBREF31 as the main metrics. Apart from these classic metrics, we also include a novel embedding-based metric named BERTScore BIBREF32. To make the comparisons more clear, we show the delta of BERTScore results by subtracting the score of merely using input concept-sets as target sentences, named $\triangle $BERTS.
For automatically evaluating our methods, we propose to use widely used metric for image/video captioning. This is because the proposed CommonGen task can be regarded as also a caption task where the context are incomplete scenes with given concept-sets. Therefore, we choose BLEU-3/4 BIBREF28, ROUGE-2/L BIBREF29, CIDEr BIBREF30, and SPICE BIBREF31 as the main metrics. Apart from these classic metrics, we also include a novel embedding-based metric named BERTScore BIBREF32. To make the comparisons more clear, we show the delta of BERTScore results by subtracting the score of merely using input concept-sets as target sentences, named $\triangle $BERTS.
Answer: The answers are shown as follows:
* BLEU-3/4
* ROUGE-2/L
* CIDEr
* SPICE
* BERTScore
Question: Extract the ingredients in a Manhattan cocktail from this text and present them in a bulleted list.
Evidence: A Manhattan is a cocktail made with whiskey, sweet vermouth, and bitters. While rye is the traditional whiskey of choice, other commonly used whiskies include Canadian whisky, bourbon, blended whiskey, and Tennessee whiskey. The cocktail is usually stirred then strained into a cocktail glass and garnished traditionally with a maraschino cherry. A Manhattan may also be served on the rocks in a lowball glass.
Answer: The ingredients in a Manhattan cocktail are:
- whiskey (rye, Canadian, bourbon, blended, Tennessee)
- sweet vermouth
- bitters
- maraschino cherry (garnish)
Question: How do their interpret the coefficients?
Evidence: We will apply the methodology to the well-known “Swissmetro" dataset. We will compare it with a dummy variables and PCA baselines. We will follow the 3-way experimental design mentioned before: split the dataset into train, development and test sets, so that the embeddings, PCA eigenvectors and the choice model are estimated from the same train and development sets, and validate it out-of-sample. For the sake of interpretability, we will also project back coefficients from the embeddings as well as PCA models into the dummy variable space.
For the sake of interpretability, we will also project back coefficients from the embeddings as well as PCA models into the dummy variable space.
Answer: The coefficients are projected back to the dummy variable space.
Question: What is the difference between AWD and 4WD?
Answer: AWD is a system that without driver intervention, shifts power between the rear and front wheels. This system is typically found on light-duty SUVs or passenger cars. The AWD drive system is designed for mild inclement weather conditions such as light snow, ice and rain. It is not designed for off-roading or severe weather conditions such as heavy snow or mud. This is where the 4WD system comes into the picture. 

4WD is a system that includes a transfer case that directly applies power to the rear axle, both front and rear axles and in some cases, only to the front axle. In addition, some 4WD systems include lower gear ratio options, locking hubs and lockers in the axles that force an equal amount of power to each wheel. All this taken together enables a 4WD system to enable a vehicle to navigate through deep snow, mud, over rocks and other obstacles with ease. The 4WD system is most commonly found on trucks, Jeeps and other purpose-built vehicles designed for heavy-duty use, whether for work or pleasure.
Question: Who was Ann-Marie Hermans?
Evidence: Ann-Marie Hermans is an Australian politician. She is a member of the Liberal Party and is a member of the Victorian Legislative Council, representing the South Eastern Metropolitan Region since November 2022. Upon election to the Legislative Council, she was appointed Shadow Minister for Emergency Services and Shadow Minister for WorkCover and the TAC in the Pesutto shadow cabinet. Before joining the Liberals, she ran for Family First at the 2006 Victorian state election.

Hermans was a school teacher prior to entering politics.
Answer: Ann-Marie Hermans is an Australian politician from the Liberal Party. She has represented the South Eastern Metropolitan Region since November 2022.
Question: Is Paris a good city to live in?
Answer: Paris is the so called city of light. Other people call it the museum city. The reason for this is that you can find art in almost every corner in Paris, and beauty is everywhere. However, the price for living in the city can be very high. It would be a good city lo live in if you enjoy being surrounded by culture, art, good restaurants and museums; however, you have to take into account that you will probably be living surrounded by tourist and paying a very high price.
Question: Classify each of the following as either a state or a city
Answer: Virginia, Houston, Florida, Los Angeles, Chicago, Phoenix, California
Question: Which machine learning models do they use to correct run-on sentences?
Evidence: In this paper, we analyze the task of automatically correcting run-on sentences. We develop two methods: a conditional random field model (roCRF) and a Seq2Seq attention model (roS2S) and show that they outperform models from the sister tasks of punctuation restoration and whole-sentence grammatical error correction. We also experiment with artificially generating training examples in clean, otherwise grammatical text, and show that models trained on this data do nearly as well predicting artificial and naturally occurring run-on sentences.
In this paper, we analyze the task of automatically correcting run-on sentences. We develop two methods: a conditional random field model (roCRF) and a Seq2Seq attention model (roS2S) and show that they outperform models from the sister tasks of punctuation restoration and whole-sentence grammatical error correction.
Answer: The answers are shown as follows:
* conditional random field model
* Seq2Seq attention model
Question: Provide few tips and techniques for Partner Ecosystem Enablement
Answer: Partner enablement involves providing your business partners with the tools, training, and resources they need to effectively sell and promote your products or services. Here are some ideas for partner enablement:

Product training: Provide your partners with training on your products or services, including features and benefits, use cases, and value propositions. This can help them better understand your offerings and communicate their value to potential customers.

Sales training: Offer sales training to help partners develop their selling skills and techniques, such as objection handling, solution selling, and consultative selling. This can help them better engage with customers and close more deals.

Marketing collateral: Provide partners with marketing collateral, such as brochures, case studies, and white papers, that they can use to promote your products or services to their customers. Make sure the materials are customized to their needs and aligned with their messaging.

Co-marketing opportunities: Work with partners to develop co-marketing campaigns, such as webinars, events, or joint advertising efforts, that can help generate leads and raise awareness of your products or services.

Technical support: Offer technical support to partners, such as documentation, training, and access to your technical team, to help them better integrate and use your products or services in their solutions.

Incentives and rewards: Provide partners with incentives and rewards, such as discounts, rebates, or sales incentives, to motivate them to sell and promote your products or services.

Partner portals: Create a partner portal that provides partners with access to resources, training materials, and other information they need to effectively sell and promote your products or services.