DataHammer/scimrc huggingface dataset:
Question: First you'd need to consider what you're using it for. Exercise bikes can be very different from commuters or casual ride bikes or velodrome racers. Another consideration is budget: bikes can range from a couple hundred dollars in price to several thousand. Accessories can dramatically increase the price as well.

For general, all-purpose bikes you may want to consider a commuter bicycle. It would have a wider, thicker wheel than a road bike so it would be a little sturdier for urban roads. They tend to be a bit heavier, so there is a tradeoff.
Answer: There isn't any one bicycle that would be ideal for all people. Bike shops have experts who can advise the right model and size for you and your main uses. You could also look at product results from online bike shops and read reviews to supplement the advice from the shop. A meetup or ride with a local cycling group would be another great source of advice and targeted knowledge for making a decision which bike is right for you.
Question: What do colleges consider as part of their admissions process?
Answer: Colleges consider the following when considering whether to accept or reject an applicant:
1. GPA
2. Test scores (e.g., SAT, ACT)
3. Extracurricular activities
4. Application essay
Question: Given a reference text about coleus rotundifolius, what are they commonly known as?
Evidence: Coleus rotundifolius, synonyms Plectranthus rotundifolius and Solenostemon rotundifolius, commonly known as native or country potato in Africa and called Chinese potato in India, is a perennial herbaceous plant of the mint family (Lamiaceae) native to tropical Africa. It is cultivated for its edible tubers primarily in West Africa, as well as more recently in parts of Asia, especially India, Sri Lanka, Malaysia, and Indonesia.

C. rotundifolius is closely related to the coleus plants widely cultivated as ornamentals and is now again placed in the genus Coleus, after being placed in the defunct genus Solenostemon and in Plectranthus.
Answer: Coleus rotundifolius are commonly known as country potato in Africa and Chinese potato in India.
Question: What are strong baseline models in specific tasks?
Evidence: Since BERT has already achieved the state-of-the-art performance of question-answering, in this section we compare our proposed model with state-of-the-art question answering models (i.e. QANet BIBREF39) and BERT-Base BIBREF26. As BERT has two versions: BERT-Base and BERT-Large, due to the lack of computational resource, we can only compare with BERT-Base model instead of BERT-Large. Prediction layer is attached at the end of the original BERT-Base model and we fine tune it on our dataset. In this section, the named entity integration method is chosen to pure concatenation (Concatenate the named entity information on pathology report text and query text first and then concatenate contextualized representation and concatenated named entity information). Comparative results are summarized in Table TABREF23.
Since BERT has already achieved the state-of-the-art performance of question-answering, in this section we compare our proposed model with state-of-the-art question answering models (i.e. QANet BIBREF39) and BERT-Base BIBREF26. As BERT has two versions: BERT-Base and BERT-Large, due to the lack of computational resource, we can only compare with BERT-Base model instead of BERT-Large.
Answer: The answers are shown as follows:
* state-of-the-art question answering models (i.e. QANet BIBREF39) and BERT-Base BIBREF26
Question: How to be rich?
Answer: While many people aspire to become rich, the reality is that it's an elusive dream for most of all, as less than 1% of the population ever achieve true wealth. It's important to acknowledge that not everyone can become rich, and that financial success is not the only measure of a fulfilling life. However, having a job that can sustain your daily life and your family is a good starting point. From there, you can think about ways to promote yourself and increase your income. It's also important to remember that richness is not just about money; emotional wealth, such as living a happy and fulfilling life and having no regrets, is also a form of richness.
Question: What is the correlation of their metric SERA with ROUGE-2 and ROUGE-3?
Evidence: Table TABREF25 shows correlations of our metric Sera with Rouge-2 and Rouge-3, which are the highest correlated Rouge variants with pyramid. We can see that in general, the correlation is not strong. Keyword based reduction variants are the only variants for which the correlation with Rouge is high. Looking at the correlations of KW variants of Sera with pyramid (Table TABREF23 , bottom part), we observe that these variants are also highly correlated with manual evaluation.
Table 3 shows correlations of our metric SERA with ROUGE-2 and ROUGE-3, which are the highest correlated ROUGE variants with pyramid. We can see that in general, the correlation is not strong. Keyword based reduction variants are the only variants for which the correlation with ROUGE is high. Looking at the correlations of KW variants of SERA with pyramid (Table 2, bottom part), we observe that these variants are also highly correlated with manual evaluation.
Answer: It is not strong in general, Only keyword-based reduction variants have high correlation with ROUGE.
Question: Do George Lucas and Steven Spielberg know each other?
Answer: Yes, George Lucas and Steven Spielberg are long-time friends, dating back to their first meeting in 1967. They have collaborated and supported each other on a number of films and celebrated each others success in the field of filmmaking.
Question: What recommendations are made to improve the performance in future?
Evidence: From the error analysis, we conclude that category I errors need further investigation, as here the model makes mistakes on seemingly easy instances. This might be due to the model not being able to correctly represent Twitter specific language or unknown words, such as Eukraine in example e). Category II and III errors are harder to avoid and could be improved by applying reasoning BIBREF36 or irony detection methods BIBREF37.
Category II and III errors are harder to avoid and could be improved by applying reasoning BIBREF36 or irony detection methods BIBREF37.
Answer: The answers are shown as follows:
* applying reasoning BIBREF36 or irony detection methods BIBREF37
Question: What type and size of word embeddings were used?
Evidence: We used the public tool, word2vec, released by Mikolov-2013 to obtain the word embeddings. Their neural network approach is similar to the feed-forward neural networks BIBREF5 , BIBREF6 . To be more precise, the previous words to the current word are encoded in the input layer and then projected to the projection layer with a shared projection matrix. After that, the projection is given to the non-linear hidden layer and then the output is given to softmax in order to receive a probability distribution over all the words in the vocabulary. However, as suggested by Mikolov-2013, removing the non-linear hidden layer and making the projection layer shared by all words is much faster, which allowed us to use a larger unlabeled corpus and obtain better word embeddings.
Among the methods presented in Mikolov-2013, we used the continuous Skip-gram model to obtain semantic representations of Turkish words. The Skip-gram model uses the current word as an input to the projection layer with a log-linear classifier and attempts to predict the representation of neighboring words within a certain range. In the Skip-gram model architecture we used, we have chosen 200 as the dimension of the obtained word vectors. The range of surrounding words is chosen to be 5, so that we will predict the distributed representations of the previous 2 words and the next 2 words using the current word. Our vector size and range decisions are aligned with the choices made in the previous study for Turkish NER by Demir-2014. The Skip-gram model architecture we used is shown in Figure FIGREF3 .
We used the public tool, word2vec, released by Mikolov-2013 to obtain the word embeddings. Their neural network approach is similar to the feed-forward neural networks BIBREF5 , BIBREF6 .
In the Skip-gram model architecture we used, we have chosen 200 as the dimension of the obtained word vectors.
Answer: The answers are shown as follows:
* word2vec
* 200 as the dimension of the obtained word vectors
Question: How has McDonald's target audience changed over time?
Evidence: Fast food restaurants often aim some of their advertising directly at the youth population. McDonald's Happy Meals, which include a toy often tied in with a newly released family film, is a significant example. Ronald McDonald, a clown advertising mascot introduced in 1963 and designed to appeal to young children, is another. In addition, in 1987 McDonald's incorporated a Play Place in their restaurants to further advertise to children, making their restaurants a more appealing environment for children. Additionally, from 1996 to 2006, Disney was an exclusive partner with McDonald's, linking their products together. They announced the end of this deal in May 2006, with some reports saying that Disney was worried about childhood obesity. Other than Disney, McDonald's has also been partnered with Nintendo since 1985, when the Nintendo Entertainment System was first introduced. In 1987, McDonald's also created a Nintendo play land in their restaurants where kids could play on Nintendo consoles while waiting for their food. During 2007, McDonald's began to provide WiFi from the Nintendo consoles; giving children the ability to play wherever they were. With also a target audience of children releasing these new films and incorporating toys, it uses the kids to reach out to their parents pockets because of their large investment.
Answer: McDonald's has consistently aimed their advertising directly at the youth population.

Starting in 1963, they introduced Ronald McDonald, a clown advertising mascot designed to appeal to young children. Over the years, McDonald's partnered with multiple companies that have products targeted at children, such as Nintendo and Disney.
Question: Give me a list of video game systems from the past few decades
Answer: 1) Atari
2) Nintendo
3) Sega
4) Sega Genesis
5) Super Nintendo
6) Sony Playstation
7) Sony Playstation 2
8) N64
9) Neo-Geo
10) Sega Saturn
11) Sega Gamecube
12) Nintendo Switch
13) Nintendo Wii
14) Playstation 3
15) Playstation 4
16) Playstation 5
17) MSFT XBox
18) MSFT Xbox One
Question: What are the most common injuries in rowing?
Evidence: Rowing is a low-impact sport with movement only in defined ranges, so that twist and sprain injuries are rare. However, the repetitive rowing action can put strain on knee joints, the spine and the tendons of the forearm, and inflammation of these are the most common rowing injuries. If one rows with poor technique, especially rowing with a curved rather than straight back, other injuries may surface, including back pains and wrist injuries. Blisters occur for almost all rowers, especially in the beginning of one's rowing career, as every stroke puts pressure on the hands, though rowing frequently tends to harden hands and generate protective calluses. Holding the oars too tightly or making adjustments to technique may cause recurring or new blisters, as it is common to feather the blade. Another common injury is getting "track bites", thin cuts on the back of one's calf or thigh caused by contact with the seat tracks at either end of the stroke.
Answer: The most common injuries in rowing are inflammation of the knees, spine and forearms. Oher common injuries also include hand blisters and track bites.
Question: How do they measure the quality of detection?
Evidence: Our goal is to compare the efectiviness of the proposed approach against the baseline system described in BIBREF13 . We evaluate the false-reject (FR) and false-accept (FA) tradeoff across several end-to-end models of distinct sizes and computational complexities. As can be seen in the Receiver Operating Characteristic (ROC) curves in Figure FIGREF14 , the 2 largest end-to-end models, with 2-stage training, significantly outperform the recognition quality of the much larger and complex Baseline_1850K system. More specifically, E2E_318K_2stage and E2E_700K_2stage show up to 60% relative FR rate reduction over Baseline_1850K in most test conditions. Moreover, E2E_318K_2stage uses only about 26% of the computations that Baseline_1850K uses (once normalizing their execution rates over time), but still shows significant improvements. We also explore end-to-end models at a size that, as described in BIBREF7 , is small enough, in both size and computation, to be executed continuously with very little power consumption. These 2 models, E2E_40K_1stage and E2E_40K_2stage, also explore the capacity of end-to-end training (1stage) versus encoder+decoder training (2stage). As can be appreciated in the ROC curves, 1stage training outperforms 2stage training on all conditions, but particularly on both "clean" environments where it gets fairly close to the performance of the baseline setup. That is a significant achievement considering E2E_40K_1stage has 2.3% the parameters and performs 3.2% the computations of Baseline_1850K. Table TABREF13 compares the recognition quality of all setups by fixing on a very low false-accept rate of 0.1 FA per hour on a dataset containing only negative (i.e. non-keyword) utterances. Thus the table shows the false-reject rates at that operating point. Here we can appreciate similar trends as those described above: the 2 largest end-to-end models outperforms the baseline across all datasets, reducing FR rate about 40% on the clean conditions and 40%-20% on the other 2 sets depending on the model size. This table also shows how 1stage outperforms 2stage for small size models, and presents similar FR rates as Baseline_1850K on clean conditions.
Our goal is to compare the efectiviness of the proposed approach against the baseline system described in BIBREF13 . We evaluate the false-reject (FR) and false-accept (FA) tradeoff across several end-to-end models of distinct sizes and computational complexities. As can be seen in the Receiver Operating Characteristic (ROC) curves in Figure FIGREF14 , the 2 largest end-to-end models, with 2-stage training, significantly outperform the recognition quality of the much larger and complex Baseline_1850K system. More specifically, E2E_318K_2stage and E2E_700K_2stage show up to 60% relative FR rate reduction over Baseline_1850K in most test conditions. 
Answer: The answers are shown as follows:
* We evaluate the false-reject (FR) and false-accept (FA) tradeoff across several end-to-end models of distinct sizes and computational complexities.
Question: Who played Dr. Jerry Buss in the show Winning Time?
Answer: John C. Reilly
Question: What are the generations of the Ford Bronco?
Answer: 1966-1977 Generation 1 (also considered EB or Early Broncos)
1978-1979 Generation 2
1980-1986 Generation 3 (also called bull nose)
1987-1991 Generation 4 (also called brick nose)
1992-1996 Generation 5
2021-Present Generation 6 (also called new bronco)
Question: How does the time of sunrise vary from spring to summer?
Evidence: Although the Sun appears to "rise" from the horizon, it is actually the Earth's motion that causes the Sun to appear. The illusion of a moving Sun results from Earth observers being in a rotating reference frame; this apparent motion caused many cultures to have mythologies and religions built around the geocentric model, which prevailed until astronomer Nicolaus Copernicus formulated his heliocentric model in the 16th century.
Astronomically, sunrise occurs for only an instant: the moment at which the upper limb of the Sun appears tangent to the horizon. However, the term sunrise commonly refers to periods of time both before and after this point:
Twilight, the period in the morning during which the sky is brightening, but the Sun is not yet visible. The beginning of morning twilight is called astronomical dawn.
The period after the Sun rises during which striking colors and atmospheric effects are still seen.
The timing of sunrise varies throughout the year and is also affected by the viewer's latitude and longitude, altitude, and time zone. These changes are driven by the axial tilt of Earth, daily rotation of the Earth, the planet's movement in its annual elliptical orbit around the Sun, and the Earth and Moon's paired revolutions around each other. The analemma can be used to make approximate predictions of the time of sunrise.
In late winter and spring, sunrise as seen from temperate latitudes occurs earlier each day, reaching its earliest time near the summer solstice; although the exact date varies by latitude. After this point, the time of sunrise gets later each day, reaching its latest sometime around the winter solstice. The offset between the dates of the solstice and the earliest or latest sunrise time is caused by the eccentricity of Earth's orbit and the tilt of its axis, and is described by the analemma, which can be used to predict the dates.
Variations in atmospheric refraction can alter the time of sunrise by changing its apparent position. Near the poles, the time-of-day variation is exaggerated, since the Sun crosses the horizon at a very shallow angle and thus rises more slowly.
Accounting for atmospheric refraction and measuring from the leading edge slightly increases the average duration of day relative to night. The sunrise equation, however, which is used to derive the time of sunrise and sunset, uses the Sun's physical center for calculation, neglecting atmospheric refraction and the non-zero angle subtended by the solar disc.
Answer: In late winter and spring, sunrise as seen from temperate latitudes occurs earlier each day, reaching its earliest time near the summer solstice; although the exact date varies by latitude. After this point, the time of sunrise gets later each day, reaching its latest sometime around the winter solstice.
Question: Which are the main reasons for doing a PhD?
Answer: A PhD degree is an essential qualification and prerequisite towards the Academia carrier; in order to be able to teach University students and also progress the research interests and activities. From the first semesters of the PhD studies, candidates will be encouraged to practice their teaching skills, by giving seminars or lectures to undergraduate students.
Question: What are three tips to a successful fishing outing?
Answer: 1. Be prepared. Check the weather and ensure you have adequate clothing for the expected weather. Bring enough food and water to keep yourself comfortable while out on the boat.
2. Go at the best time of day. Most freshwater fish have a relatively predictable daily routine and will bite best very early in the morning (just before or at sunrise) and later in the evening, a couple hours before sunset.
3. Fish in the right place! Most freshwater fish have an environment preference. For example, summer bass like to be in weeds and other cover; spring walleye can be found in more shallow water with sandy/rocky bottoms; fall pike and musky ambush prey from thick weed beds. If you want to catch a lot of fish, you need to be fishing where the fish are!
Question: Categorize each of the vehicles as a car, truck, or van: Tesla Model 3, Ford F150, Chevy Silverado, Toyota Sienna, Honda Odyssey, Toyota Tacoma, Dodge Dart
Answer: Tesla Model 3: Car
Ford F150: Truck
Chevy Silverado: Truck
Toyota Sienna: Van
Honda Odyssey: Van
Toyota Tacoma: Truck
Dodge Dart: Car
Question: Rewrite the following sentence in terms of horses, rather than dogs: "The adjective form of dog is canine."
Answer: The adjective form of horse is equine.
Question: What are some things that people commonly add to beer?
Answer: The most common things to add into beer are slices of citrus fruit, like lime, orange, or lemon. Sometimes juice is added to beer as well, such as orange juice for a brass monkey, frozen lime juice for a beer margarita, tomato and lime juice for a michelada, or lemon juice for a radler.
Question: Who is the greatest NBA player of all time?
Answer: The debate regarding who is the greatest NBA player of all time generally revolves around defining what criteria should be used to rank basketball players. Factors such as number of championships won, individual accolades, career statistics, longevity, and the level to which a player's level of play dominated over their contemporaries are common criteria for determining who is the greatest NBA player of all time. However, this question is complicated by others who state that comparing players across different generations is not possible, and thus the debate should be focused on who is the greatest player within a given generation.

The NBA.com website states that "By acclamation, Michael Jordan is the greatest basketball player of all time". Jordan's perfect record in the finals, dominance over contemporaries (many of whom did not win any championships during the years Jordan was active), and holding the highest career regular season scoring average are often used to justify his status as the greatest NBA player of all time. Other frequently mentioned greats include Kareem Abdul-Jabbar, Wilt Chamberlain, and LeBron James.
Question: What is a hockey hat trick ?
Answer: when a player scores three goals in a game, usually earning him a cascade of hats thrown onto the ice by fans (especially if the player is on the home team). A natural hat trick is when a player scores three consecutive goals in a game.
Question: Which cities did some of the most famous English rock bands come from?
Answer: Cities that some of the most famous English rock bands came from are Liverpool (The Beatles), London (Led Zeppelin, The Rolling Stones, The Who, Pink Floyd, Queen, Deep Purple), Sheffield (Def Leppard), Birmingham (Black Sabbath), and Manchester (Oasis).
Question: Karl Lienstater discovered which medical breakthrough in 1901
Answer: ABO Blood Groups
Question: Why you need to save Money
Answer: Because  you need it for emergency . You do not know you can not earn money always.
Question: Identify the bird from the list: Queensbury, Kingfisher, Bishopsgate
Answer: Kingfisher
Question: Write a short story about a person who discovers a bowling ball with special powers to roll strikes every time. The story should include a plot twist and a clear resolution at the end.
Answer: It seemed like any other day as Kyle and Jeff headed to Airway Lanes for a fun time at the bowling alley. While meticulously looking over house balls with fingertip grips to feel like the pros, Jeff found one that caught his eye. The beautiful blue ball, with pink swirls and matching holes, already somehow had his same initials carved in.

As the two began to bowl, Jeff started with a strike. "Oh, I like this one," he thought. Another strike! "I could get used to this," he told himself.

Kyle was also bowling well, notching a strike and a 9-spare but nothing like what Jeff was doing on the lanes this fateful afternoon.

As Jeff lined up for his 3rd roll, his palms started sweating. The dreaded Turkey is where he got stuck so many times. But not today... ANOTHER STRIKE! Jeff jumped for joy. 

The two would go on to bowl their best games ever, a perfect 300 for Jeff and 279 for Kyle. 

As Jeff headed home, he wondered if his new ball, which the bowling alley gave him after his perfect game, was magical. 

He headed back to the lanes the next day. Again nothing but strikes. As Jeff figured out there was something magical about the ball, he had the decision to make. He could go on to be the best bowler never, never missing a pin again. Or, he could get a ball that wasn't magical. And play with honor. 

Jeff decided to destroy the ball for the good of mankind. And continue his craft the good old fashion way, with hard work and dedication!
Question: What are the names of Daenerys Targaryen's three dragons?
Answer: Drogon, Viserion, and Rhaegal