DataHammer/scimrc huggingface dataset:
Question: How many convolutional layers does their model have?
Evidence: Given raw audio samples INLINEFORM0 , we apply the encoder network INLINEFORM1 which we parameterize as a five-layer convolutional network similar to BIBREF15 . Alternatively, one could use other architectures such as the trainable frontend of BIBREF24 amongst others. The encoder layers have kernel sizes INLINEFORM2 and strides INLINEFORM3 . The output of the encoder is a low frequency feature representation INLINEFORM4 which encodes about 30ms of 16KHz of audio and the striding results in representation INLINEFORM5 every 10ms.
Next, we apply the context network INLINEFORM0 to the output of the encoder network to mix multiple latent representations INLINEFORM1 into a single contextualized tensor INLINEFORM2 for a receptive field size INLINEFORM3 . The context network has seven layers and each layer has kernel size three and stride one. The total receptive field of the context network is about 180ms.
Given raw audio samples INLINEFORM0 , we apply the encoder network INLINEFORM1 which we parameterize as a five-layer convolutional network similar to BIBREF15 .
Next, we apply the context network INLINEFORM0 to the output of the encoder network to mix multiple latent representations INLINEFORM1 into a single contextualized tensor INLINEFORM2 for a receptive field size INLINEFORM3 . The context network has seven layers and each layer has kernel size three and stride one. 
Answer: wav2vec has 12 convolutional layers
Question: Give me a list of some characteristics of a good coffee shop?
Answer: Some characteristics of good coffee shops include:
- Very good coffee, either freshly roasted locally or acquired from a quality roaster
- High end coffee grinders, brewing machines, and a high quality espresso machine and well-trained baristas
- Different coffee roast options (i.e. medium roast, dark roast) and brewing methods (i.e. drip coffee and pour-over) available
- A variety of cafe fare, such as pastries and croissants, available for purchase to accompany coffee
- Ample seating, with power outlets available by most seats.
Question: Why do people like gardening?
Answer: People like to garden to grow their own food, flowers, and medicine, as well as experience the outdoors and natural ecosystems around us.  Some also like to garden to improve the aesthetics and monetary value of their property.
Question: What is prize money for Abel Prize ?
Answer: 7 million NOK(Norwegian Krone)
Question: What is YouTube?
Answer: YouTube is a consumer video-sharing platform owned by Alphabet.
Question: Give me a list of the venues that were used for the US Open Golf tournament through the years 1991 - 1995
Answer: 1991 - Hazeltine National Golf Club
1992 - Pebble Beach Golf Links
1993 - Baltusrol Golf Club (Lower Course)
1994 - Oakmont Country Club
1995 - Shinnecock Hills Golf Club
Question: What are some common items on a charcuterie board?
Answer: Common items on a charcuterie board include slice cured sausage, pepperoni, goat cheese, manchengo cheese, white cheddar, prosciutto, baby dill pickles, dried apricots, grapes, jam, crackers, and chocolate covered almonds.
Question: Give me some ideas of things to do this weekend.
Answer: Congratulations on a well-deserved weekend break. Some ideas of things to try:
1. Get outdoors. Go for a hike or run.
2. Get social. Meet friends and family for celebrations and to strengthen bonds. 
3. Go, volunteer. Support a cause that is close to you and make a positive impact in our world!
4. Go on a road trip. Experience and memories help us recharge and support our mental health. 
5. Learn something new. Continual learning keeps us interested and engaged. New skills and hobbies can keep life fun and open new doors. 
6. Participate in sports. You can participate in sporting activities to stay engaged or watch and cheer on your favorite teams. 
7. See a movie or watch your favorite shows. Enjoy a good tale and find novelty from the comfort of your living room or the rich audio-visual cinema experience nearby!
Question: Who directed the most episodes of season five of Game of Thrones?
Answer: No one director had more episodes than any other in season five of Game of Thrones. Of the ten episodes, there were five directors who each directed two episodes: Michael Slovis, Mark Mylod, Jeremy Podeswa, Miguel Sapochnik, and David Nutter.
Question: Which is a species of fish? Escolar or Escobar
Answer: Escolar
Question: what causes leaves to change color in the fall season
Answer: Leaves of trees are green in color most of the year because of chlorophyll. Chlorophyll is used during the photosynthesis process to absorb energy from sunlight which is then converted to sugars that provides trees with the nutrition it needs much like humans do

In the fall, as the days gets shorter and temperature drops trees get less direct sunlight and also not much heat elsewhere which starts to break down the chlorophyll. This lack of chlorophyll causes pigmentation in the leaves which makes it turn yellow & orange
Question: What events are included in an Olympic Decathlon?
Answer: The Olympic Decathlon is comprised of the following 10 events:

1. 100-Meter Dash
2. Long Jump
3. Shot Put
4. High Jump
5. 400-Meter Dash
6. 110-Meter Hurdles
7. Discus Throw
8. Pole Vault
9. Javelin Throw
10. 1,500-Meter Run
Question: What is constitution?
Answer: A constitution is the aggregate of fundamental principles or established precedents that constitute the legal basis of a polity, organisation or other type of entity and commonly determine how that entity is to be governed
Question: What analysis was performed to get an insight into the contribution of different contexts to the resolution of blanks?
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 ).
To get an insight into the contribution of different contexts to the resolution of blanks, we performed manual analysis of examples coming from the English-German base, del and del+obj setups (50 random examples per setup), where we count correctly translated blanks per system.
Answer: Manual analysis of examples coming from the English-German base, del and del+obj setups (50 random examples per setup).
Question: From the passage provided, extract the company that all original presto developers joined in 2020
Evidence: Presto was originally designed and developed at Facebook, Inc. (later renamed Meta) for their data analysts to run interactive queries on its large data warehouse in Apache Hadoop. The first four developers were Martin Traverso, Dain Sundstrom, David Phillips, and Eric Hwang. Before Presto, the data analysts at Facebook relied on Apache Hive for running SQL analytics on their multi-petabyte data warehouse. Hive was deemed too slow for Facebook's scale and Presto was invented to fill the gap to run fast queries. Original development started in 2012 and deployed at Facebook later that year. In November 2013, Facebook announced its open source release.

In 2014, Netflix disclosed they used Presto on 10 petabytes of data stored in the Amazon Simple Storage Service (S3). In November, 2016, Amazon announced a service called Athena that was based on Presto. In 2017, Teradata spun out a company called Starburst Data to commercially support Presto, which included staff acquired from Hadapt in 2014. Teradata's QueryGrid software allowed Presto to access a Teradata relational database.

In January 2019, the Presto Software Foundation was announced. The foundation is a not-for-profit organization for the advancement of the Presto open source distributed SQL query engine. At the same time, Presto development forked: PrestoDB maintained by Facebook, and PrestoSQL maintained by the Presto Software Foundation, with some cross pollination of code.

In September 2019, Facebook donated PrestoDB to the Linux Foundation, establishing the Presto Foundation. Neither the creators of Presto, nor the top contributors and committers, were invited to join this foundation.

By 2020, all four of the original Presto developers had joined Starburst. In December 2020, PrestoSQL was rebranded as Trino, since Facebook had obtained a trademark on the name "Presto" (also donated to the Linux Foundation).

Another company called Ahana was announced in 2020, with seed funding from GV (formerly Google Ventures, an arm of Alphabet, Inc.), to commercialize the PrestoDB fork as a cloud service, while also offering an open-source version. A $20 million round of funding for Ahana was announced in August 202
Answer: Starburst
Question: Why do sailboats have to tack upwind?
Answer: Modern sailboats use sails that act as foils, with pressure that increases on the inside of the foil higher than the outside of the foil, similar to an airplane wing and described by the Bernoulli effect.  The sails must have an angle of attack that is perpendicular to the direction of the wind to be effective.  Off the wind, or heading away from the wind, the sails can be eased out to maintain this angle.  Heading into the wind, the boat can only get so close to the direction to keep the sails from becoming ineffective or "luffing."  So to head in the general direction of the wind, a boat must tack at angles to the wind, to make its way in the direction of the wind.
Question: Classify each of the following as either a dog breed or cat breed: german shepherd, bulldog, labrador retriever, french bulldog, siberian husky, alaskan malamute, poodle, chihuahua, rottweiler, british shorthair, maine coon, persian, ragdoll, sphynx, american shorthair, birman, russian blue
Answer: german shepherd - dog, bulldog - dog, labrador retriever - dog, french bulldog - dog, siberian husky - dog, alaskan malamute - dog, poodle - dog, chihuahua - dog, rottweiler - dog, british shorthair - cat, maine coon - cat, persian - cat, ragdoll - cat, sphynx - cat, american shorthair - cat, birman - cat, russian blue - cat
Question: Q: Am I at risk for serious complications from COVID-19 if I smoke cigarettes?
Answer: A: Yes. Data shows that when compared to never smokers, cigarette smoking increases the risk of more severe illness from COVID-19, which could result in hospitalization, the need for intensive care, or even death. Smoking cigarettes can cause inflammation and cell damage throughout the body, and can weaken your immune system, making it less able to fight off disease.

There’s never been a better time to quit smoking. If you need resources to help you quit smoking, the FDA has supportive tips and tools to help you get closer to quitting for good.
Question: What is a speedrun in video games?
Answer: In gaming, a speedrun is the task of playing a game, or a section of a game, with the goal of completing it as quickly as possible. While there are many categories of speedrunning, they often include strategy, planned routes, or even glitches to get to the end credits of the game in the shortest possible time.
Question: What was performance of classifiers before/after using distant supervision?
Evidence: The experimental results for Yorùbá are given in Figure FIGREF11. The setting differs from the experiments with Hausa in that there is a small clean training set and additional, distantly-supervised data. For the Bi-LSTM model, adding distantly-supervised labels always helps. In the low-resource settings with 1k and 2k labeled data, it more than doubles the performance. Handling the noise in the distant supervision can result in slight improvements. The noise-cleaning approach struggles somewhat while the confusion matrix architecture does give better results in the majority of the scenarios. Training on 5k labeled data with distantly supervised data and noise handling, one can obtain a performance close to using the full 17k manually labeled token.
FLOAT SELECTED: Figure 1: F1-scores and standard error for Yorùbá.
The experimental results for Yorùbá are given in Figure FIGREF11. The setting differs from the experiments with Hausa in that there is a small clean training set and additional, distantly-supervised data. For the Bi-LSTM model, adding distantly-supervised labels always helps. In the low-resource settings with 1k and 2k labeled data, it more than doubles the performance. Handling the noise in the distant supervision can result in slight improvements. The noise-cleaning approach struggles somewhat while the confusion matrix architecture does give better results in the majority of the scenarios. Training on 5k labeled data with distantly supervised data and noise handling, one can obtain a performance close to using the full 17k manually labeled token.
FLOAT SELECTED: Figure 1: F1-scores and standard error for Yorùbá.
Answer: Bi-LSTM: For low resource <17k clean data: Using distant supervision resulted in huge boost of F1 score (1k eg. ~9 to ~36 wit distant supervision)
BERT: <5k clean data boost of F1 (1k eg. ~32 to ~47 with distant supervision)
Question: What is JavaScript?
Answer: JavaScript, often abbreviated as JS, is a programming language that is one of the core technologies of the World Wide Web, alongside HTML and CSS. As of 2022, 98% of websites use JavaScript on the client side for webpage behavior, often incorporating third-party libraries. All major web browsers have a dedicated JavaScript engine to execute the code on users' devices.
Question: What's the best baseball team?
Answer: Denoting one baseball team as "best" is a very difficult. Many factors may be involved when determining the best baseball team. For instance, are we looking at current season performance? History of championships in the past? Number of fans? Best statistics? Most notable? Please help me by being more specific about what "best" means to you.
Question: Why is driving in convertibles fun?
Answer: Many people find driving in convertibles fun because it can be perceived as a status symbol. Convertibles tend to evoke a certain energy, both externally and internally.
Question: Are platypuses mammals or oviparous?
Answer: Platypuses are both mammals (as they raise their off-springs with maternal milk) and oviparous (as they lay eggs).
Question: Classify each of the following as an American coffee shop chain or an American fast-food hamburger restaurant: Starbucks, Dunkin Donuts, McDonald's, In-N-Out, Dutch Bros, Coffee Bean & Tea Leaf, Burger King, Carl's Jr
Answer: Coffee shop chain: Starbucks, Dunkin Donuts, Dutch Bros, Coffee Bean & Tea Leaf
Fast-food hamburger restaurant: McDonald's, In-N-Out, Burger King, Carl's Jr
Question: what is the difference between a rat and a mouse
Answer: rat is larger mammal, mice are slender in size
Question: What is the net worth of one of Taylor Swift's cats?
Evidence: Swift is known for her love of cats. Her pet cats have been featured in her visual works, and one of them is the third richest pet animal in the world with an estimated $97 million net worth.
Answer: One of Taylor Swift's cats is the third richest pet animal in the world, and it's estimated net worth is $97 million.
Question: What is the Sun?
Answer: The sun is how we refer to the star in our solar system, around which each of the planets rotate.
Question: What are the most dangerous hobbies?
Answer: Sky diving, bungie jumping, cliff jumping, open water swimming, race car driving
Question: What task in NLP do they study?
Evidence: Hierarchical Multi-label Classification (HMC) is an important task in Natural Language Processing (NLP). Several NLP problems can be formulated in this way, such as patent, news articles, books and movie genres classification (as well as many other classification tasks like diseases, gene function prediction). Also, many tasks can be formulated as hierarchical problem in order to cope with a large amount of labels to assign to the sample, in a divide and conquer manner (with pseudo meta-labels). A theoretical survey exists BIBREF0 discussing on how the task can be engaged, several approaches and the prediction quality measures. Basically, the task in HMC is to assign a sample to one or many nodes of a Directed Acyclic Graph (DAG) (in special cases a tree) based on features extracted from the sample. In the case of possible multiple parent, the evaluation of the prediction complicates heavily, for once since several paths can be taken, but only in a joining node must be considered.
The GermEval 2019 Task 1 - Shared Task on hierarchical classification of German blurbs focus on the concrete challenge of classifying short descriptive texts of books into the root nodes (subtask A) or into the entire hierarchy (subtask B). The hierarchy can be described as a tree and consisted of 343 nodes, in which there are 8 root nodes. With about 21k samples it was not clear if deep learning methods or traditional NLP methods would perform better. Especially, in the subtask A, since for subtask B some classes had only a few examples. Although an ensemble of traditional and deep learning methods could profit in this area, it is difficult to design good heterogeneous ensembles.
Our approach was a traditional NLP one, since we employed them successfully in several projects BIBREF1, BIBREF2, BIBREF3, with even more samples and larger hierarchies. We compared also new libraries and our own implementation, but focused on the post-processing of the multi-labels, since this aspect seemed to be the most promising improvement to our matured toolkit for this task. This means but also, to push recall up and hope to not overshot much over precision.
Hierarchical Multi-label Classification (HMC) is an important task in Natural Language Processing (NLP). Several NLP problems can be formulated in this way, such as patent, news articles, books and movie genres classification (as well as many other classification tasks like diseases, gene function prediction).
Answer: Hierarchical Multi-label Classification.
Question: How many characters are accepted as input of the language model?
Evidence: Instead of reading in the tokenized input text, our model reads raw utf-8 bytes. For English text in the ASCII range, this is equivalent to processing characters as individual tokens. Non-ASCII characters (e.g. accented characters, or non-Latin scripts) are typically two or three utf-8 bytes. We use a standard “transformer decoder” (a stack of transformer layers with a causal attention mask) to process the sequence $x_{0:i-1}$ and predict the following byte $x_i$. The model's prediction is an estimate of the probability distribution over all possible 256 byte values. Our input byte embedding matrix has dimensionality 256. Our byte-level transformer model has 40 standard transformer layers with hidden size 1024, filter size 8192, and 16 heads. The model has around 836M parameters, of which only 66K are byte embeddings.
Instead of reading in the tokenized input text, our model reads raw utf-8 bytes. For English text in the ASCII range, this is equivalent to processing characters as individual tokens. Non-ASCII characters (e.g. accented characters, or non-Latin scripts) are typically two or three utf-8 bytes. We use a standard “transformer decoder” (a stack of transformer layers with a causal attention mask) to process the sequence $x_{0:i-1}$ and predict the following byte $x_i$. The model's prediction is an estimate of the probability distribution over all possible 256 byte values. Our input byte embedding matrix has dimensionality 256.
Answer: The answers are shown as follows:
* input byte embedding matrix has dimensionality 256
Question: Which clustering technique do they use on partients' visits texts?
Evidence: Based on Euclidean distance between vector representations of visits we applied and compared two clustering algorithms: k-means and hierarchical clustering with Ward's method for merging clusters BIBREF23 . The similarity of these clusterings was measured by the adjusted Rand index BIBREF24 . For the final results we chose the hierarchical clustering algorithm due to greater stability.
Based on Euclidean distance between vector representations of visits we applied and compared two clustering algorithms: k-means and hierarchical clustering with Ward's method for merging clusters BIBREF23 .
Answer: The answers are shown as follows:
* k-means
* hierarchical clustering with Ward's method for merging clusters BIBREF23
Question: What books has David Duchovny written?
Answer: Holy Cow: A Modern-Day Dairy Tale and Bucky F*cking Dent
Question: Imagine you come across a time machine and that with this machine time travel is possible, however, you can only make one round trip to the past and back. What year would you travel to and why?
Answer: It would be tempting to go back in time to attempt to change or experience any number of events throughout history but I would not use the machine. I am afraid that any change to the past, no matter how small, could have unknown repercussions that spread through time and change the world as I know it, threatening those that I know and love and even my own existence.
Question: Who does what in U2?
Evidence: U2 are an Irish rock band from Dublin, formed in 1976. The group consists of Bono (lead vocals and rhythm guitar), the Edge (lead guitar, keyboards, and backing vocals), Adam Clayton (bass guitar), and Larry Mullen Jr. (drums and percussion). Initially rooted in post-punk, U2's musical style has evolved throughout their career, yet has maintained an anthemic quality built on Bono's expressive vocals and the Edge's chiming, effects-based guitar sounds. Bono's lyrics, often embellished with spiritual imagery, focus on personal and sociopolitical themes. Popular for their live performances, the group have staged several ambitious and elaborate tours over their career.
Answer: The rock band U2 features Bono on lead vocals and guitar, the Edge on lead guitar, keyboard and vocals, Adam Clayton on bass guitar and Larry Mullen Jr. on drums and percussion.
Question: Where does the word cliche come from?
Answer: Cliche comes from the sound old printing presses made when making copies.
Question: Classify each of the following pieces of equipment according to the sport they are used for, either basketball, football, or soccer: shin guards, shooting sleeve, penalty flag, corner flag, kicking tee, and goalie gloves.
Answer: The classification is as follows:
- Soccer: goalie gloves, corner flag
- Basketball: shooting sleeve
- Football: penalty flag, kicking tee
Question: What age should babies be potty trained?
Answer: When a baby is ready for potty training depends on several factors.  There is no universal answer or age that a child is ready to be potty trained.  However, some signs that a child is ready to be potty trained are signaling and/or awareness of when a child is or needs to eliminate waste.   Another factor is when the care taker has the time to dedicate to consistent practice of eliminating in a toilet instead of a diaper. Infant potty training also known as elimination communication is the practice of skipping the reliance of the usage of diapers.  In this practice, the caretaker will teach signs to the baby every time the baby eliminates in the toilet (not in a diaper) - the baby will eventually pick up these signs and give cues when they need to go.  Those that subscribe to infant potty training believe that conventional diapers train babies to ignore their natural instincts by removing the discomfort one would normally sense from having wet skin (achieved by chemicals that absorb liquid and wick moisture away from the skin found in many disposable diapers).  While infant potty training takes a lot of upfront attention and discipline, young children can be fully potty trained by 9-16 months of age.  On the other hand, potty training children that have been in diapers are usually potty trained by about 36 months of age.  There are considerable convenience trade offs to both methods.
Question: Brainstorm a list of five different animals that you could find on a farm
Answer: You could find cows, sheep, chickens, horses and ducks on a farm