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abe19be5-2f7f-44e8-bfe5-76fab8062293 | 3bf9301f-288b-450c-a87f-022f45a5d226 | 5dea0df9-1441-470b-9ca4-529f922ba1da | 2023-04-10T18:43:52.036373+00:00 | Если центральный банк резко снизит процентные ставки, это может привести к нескольким последствиям, включая увеличение инфляции. Вот несколько причин, почему это может произойти:
1. Расходы на потребление: снижение процентной ставки может стимулировать потребление, так как люди могут взять кредиты и воспользоваться др... | assistant | ru | 3 | true | false | null | false | null | {
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5c9be6ea-5e7b-4d54-86fe-28e7cb322f50 | abe19be5-2f7f-44e8-bfe5-76fab8062293 | 9db19afe-5a1b-42ca-ac2b-fcd42ae8cd47 | 2023-04-10T19:12:12.946769+00:00 | Мне интересна тема экономика и мне было интересно создать модель, описывающую экономику в рамках страны (ВВП, цб, производство и подобные вещи). Напиши пошагово что с чего мне нужно начать? | prompter | ru | 3 | true | false | null | false | null | {
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ff80110d-9236-48de-b597-25f61edc48c9 | null | 6e576cc5-5aa3-4350-b69b-45f4c469f671 | 2023-02-05T14:32:35.623818+00:00 | What are some of the overall most used classifiers in the machine learning community? Make an ordered list and describe the pros and cons for each one. | prompter | en | 3 | true | false | null | false | null | {
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456a8676-e188-46b9-8171-933585b708c6 | ff80110d-9236-48de-b597-25f61edc48c9 | f832c93e-ceba-4d69-b3c4-469f14ee7820 | 2023-03-04T19:27:22.422155+00:00 | There are many possible classifiers used but here are some of them:
### Naive Bayes Classification Algorithm
#### Advantages
- It is simple, and its implementation is straightforward.
- The time required by the machine to learn the pattern using this classifier is less.
- It performs well in the case where the input v... | assistant | en | 3 | true | false | 0 | false | null | {
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2ac7f874-43d4-4322-bcc7-bc8433c82133 | 456a8676-e188-46b9-8171-933585b708c6 | c9a9fd43-843f-4848-93f4-40572e24b5b4 | 2023-03-05T21:26:22.648355+00:00 | Which one would be best for writing a basic OCR? | prompter | en | 3 | true | false | null | false | null | {
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5f5f5bbe-d08c-4974-a634-a6b43e0efe8c | 2ac7f874-43d4-4322-bcc7-bc8433c82133 | 1aaa9be1-0d07-4cb2-a2d7-4301cbfc4ecc | 2023-03-05T23:12:09.635154+00:00 | For writing a basic OCR, the most commonly used classifier is the K-Nearest Neighbor (KNN) algorithm. KNN works by assigning a class to an object by looking at the k-nearest neighbors in the feature space. In the case of OCR, the features of the image (such as pixel values) would be used to determine the nearest neighb... | assistant | en | 3 | true | false | null | false | null | {
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e5fbf430-908c-4ddd-8f86-e3f909305f83 | 456a8676-e188-46b9-8171-933585b708c6 | 80fb9a55-a12f-4963-8f07-d270802d771b | 2023-03-05T22:10:49.911397+00:00 | What method should I use for image classification? | prompter | en | 3 | true | false | null | false | null | {
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369a022b-df50-486b-965f-b692cae0a7bb | e5fbf430-908c-4ddd-8f86-e3f909305f83 | 1aaa9be1-0d07-4cb2-a2d7-4301cbfc4ecc | 2023-03-06T00:38:50.595999+00:00 | There is no one-size-fits-all answer to this question as the choice of the method for image classification depends on several factors such as the complexity of the problem, the amount of available data, and the computational resources at hand. Here are some of the commonly used methods for image classification:
1. Con... | assistant | en | 3 | true | false | 0 | false | null | {
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5b03caaf-f546-4804-8d71-36d7598ccd0c | e5fbf430-908c-4ddd-8f86-e3f909305f83 | faa07ea2-76de-4362-a97a-bd0939d02d87 | 2023-03-05T23:58:41.226047+00:00 | There are many classifiers you can use for image classification, but the choice of a particular method will depend on your specific needs and the characteristics of your data. Some of the most popular classifiers for image classification include Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and ... | assistant | en | 3 | true | false | 1 | false | null | {
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1d72590e-41db-4ad8-ace0-997f1b4a1e8e | ff80110d-9236-48de-b597-25f61edc48c9 | 9e9664c2-a77d-4e52-978d-21cabf691987 | 2023-03-05T13:49:46.816552+00:00 | 1. Logistic Regression:
Logistic Regression is a popular classification algorithm that is used to predict the probability of a binary outcome. It is simple to implement and interpret, making it a popular choice for many applications. However, it may not perform well when there are non-linear relationships between the f... | assistant | en | 3 | true | false | 1 | false | null | {
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9690b645-9bb9-445e-8915-564062f2d3f9 | ff80110d-9236-48de-b597-25f61edc48c9 | 068951d1-4a1e-4d91-9c29-0090fdf9366d | 2023-03-04T19:14:12.844392+00:00 | Some of the most popular classifiers in machine learning, in roughly descending order of usage, are:
1. Logistic regression: Pros - Simple to train and interpret. Cons - Makes strong linear assumptions so may not fit complex data well.
2. Decision trees: Pros - Easy to interpret, can handle nonlinear data. Cons - Can ... | assistant | en | 3 | true | false | 2 | false | null | {
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3313b1fc-56fd-407b-a04a-ba370879cbf0 | 9690b645-9bb9-445e-8915-564062f2d3f9 | 3ca36df6-acd7-4893-9906-42202ad292cb | 2023-03-05T14:32:21.889967+00:00 | I don't understand how these are classifiers. What do they classify? Instead of a list, maybe you can focus on a specific example, besides neural networks? | prompter | en | 3 | true | false | null | false | null | {
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67d744a2-6169-4460-b618-1ed1c91b3e37 | 3313b1fc-56fd-407b-a04a-ba370879cbf0 | 1aaa9be1-0d07-4cb2-a2d7-4301cbfc4ecc | 2023-03-06T00:54:01.344479+00:00 | Certainly! A classifier is a machine learning algorithm that learns to distinguish between different classes or categories of data. For example, a classifier might be trained to distinguish between images of cats and dogs, or to classify email messages as spam or not spam.
Let's take the example of logistic regression... | assistant | en | 3 | true | false | 0 | false | null | {
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a4f12b92-64b3-478b-b8a1-401080b7e255 | 3313b1fc-56fd-407b-a04a-ba370879cbf0 | 99d788e6-7eb4-42c7-9dda-4cb8301dabf7 | 2023-03-06T04:50:24.355142+00:00 | I apologize for the confusion. Classifiers are algorithms used in machine learning to classify data into different categories or classes. They are used in supervised learning, where the algorithm is trained on a labeled dataset to learn to predict the correct class for new, unseen data.
Let me provide an example to ma... | assistant | en | 3 | true | false | 1 | false | null | {
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ff824123-e4dd-47f3-9968-2a50ac7a036c | null | 24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6 | 2023-02-05T22:00:27.410067+00:00 | Починаючи з якого року у Львові існує електричний трамвай? Розкажи будь ласка про його заснування | prompter | uk-UA | 3 | true | false | null | false | null | null | ff824123-e4dd-47f3-9968-2a50ac7a036c | ready_for_export | {
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"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0,
0.08333333333333333,
0... |
f5faf9f8-9fb1-45c8-8ef5-8222b482768e | ff824123-e4dd-47f3-9968-2a50ac7a036c | 24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6 | 2023-02-06T17:58:14.596679+00:00 | Систему електричного трамваю у Львові започаткували у 1894 році.
У 1893 році львівський магістрат оголосив тендер на будівництво ліній електричного трамвая та електростанції потужністю 400 кінських сил (300 кВт), бо кінний трамвай (що був відкритий у 1880 році) вже не справлявся зі зростальними потребами у перевезенн... | assistant | uk-UA | 3 | true | false | 0 | false | null | null | ff824123-e4dd-47f3-9968-2a50ac7a036c | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"quality"
],
"value": [
0,
0,
0.9166666666666666
],
"count": [
3,
3,
3
]
} |
c104ae6e-d3f1-48f6-a391-a46a6deef6b3 | f5faf9f8-9fb1-45c8-8ef5-8222b482768e | 24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6 | 2023-02-08T11:14:30.403347+00:00 | Які ще види трамваїв та інший громадський транспорт були на той час у Львові? | prompter | uk-UA | 3 | true | false | null | false | null | null | ff824123-e4dd-47f3-9968-2a50ac7a036c | ready_for_export | null | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
1,
0,
0,
0.75,
0
],
"count": [
3,... |
dea2d1b3-6495-45e4-afbd-ff247def4035 | c104ae6e-d3f1-48f6-a391-a46a6deef6b3 | 24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6 | 2023-02-08T21:49:08.547571+00:00 | Вас цікавить саме 19 століття?
Чи 20 століття також? | assistant | uk-UA | 3 | true | false | null | false | null | null | ff824123-e4dd-47f3-9968-2a50ac7a036c | ready_for_export | null | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.91666666666... |
5e121f55-1ac0-4722-90e9-4646bdb8e651 | ff824123-e4dd-47f3-9968-2a50ac7a036c | 2ee5b5a9-1998-478b-8a62-49914b3959cd | 2023-02-07T09:00:41.895697+00:00 | Електричний трамвай в Львові почав працювати в 1908 році.
Його заснування супроводжувалося виробництвом та встановленням спеціальної електротехніки. З того часу він став важливою частиною транспортної мережі Львова та допомогає містянам переміщатися з одного місця на інше.
До речі, ти знаєш, що Львівське метро - це н... | assistant | uk-UA | 3 | true | false | 1 | false | null | null | ff824123-e4dd-47f3-9968-2a50ac7a036c | ready_for_export | {
"name": [
"_skip_labeling"
],
"count": [
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0,
... |
ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | null | 91af8f77-f820-4445-b2b3-8451bbdd7c29 | 2023-02-07T15:25:21.599333+00:00 | How would I remove all lines starting with the following string in VScode? I also want to remove the empty line when deleting the text.
`this.viewTopTitle =` | prompter | en | 3 | true | false | null | false | null | {
"toxicity": 0.000329640693962574,
"severe_toxicity": 0.00003228518471587449,
"obscene": 0.0001208702742587775,
"identity_attack": 0.00013766722986474633,
"insult": 0.00015544916095677763,
"threat": 0.000048876983782975,
"sexual_explicit": 0.000027833308195113204
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
8,
6,
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5,
0.25,
0.125,
0.25,
0.125
],
"cou... |
f0406f97-d6ee-434d-965b-764b4eb3e785 | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | 4865dc11-f056-49ac-9a3a-1eda89632508 | 2023-02-08T18:19:00.902101+00:00 | To replace all lines that start with "this.view.TopTitle =" you will want to do a find and replace.
- Press Ctrl + H to open your replace panel
- In the box for selecting what to replace, type in this:
^this/.viewTopTitle=.*(\r\n|\r|\n)
- Leave the field specifying what to replace it with blank.
- Check the "Regular e... | assistant | en | 3 | true | false | 0 | false | null | {
"toxicity": 0.0006819720147177577,
"severe_toxicity": 0.000015875231838435866,
"obscene": 0.00011001012899214402,
"identity_attack": 0.00006762557313777506,
"insult": 0.00024833803763613105,
"threat": 0.000024052827939158306,
"sexual_explicit": 0.000018550403183326125
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
2,
4
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5,
0.5,... |
0449c900-b2d8-4920-a662-0511dfc1e2ad | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | e607e2c7-16ee-4354-8f87-ab5f91a82eea | 2023-02-08T16:01:01.114305+00:00 | First press, Ctrl-H to do a search and replace operation. In the search and replace widget on the top right, click the `.*` button. This enables regular expressions search.
Then in first text area of the widget enter:
`^\s*this.viewTopTitle =.*\n`
Leave the second one empty as we want to remove the whole line.
Finally... | assistant | en | 3 | true | false | 1 | false | null | {
"toxicity": 0.0003764722205232829,
"severe_toxicity": 0.0000297221358778188,
"obscene": 0.00015219271881505847,
"identity_attack": 0.00009811914787860587,
"insult": 0.00016784931358415633,
"threat": 0.00004128450382268056,
"sexual_explicit": 0.00002775900975393597
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
4,
2
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.9375,
0... |
aabb175c-8618-4a98-b6c5-d87d407bec6f | 0449c900-b2d8-4920-a662-0511dfc1e2ad | a2d24e96-207c-4d91-b452-4400fe3f3287 | 2023-02-08T21:54:39.943087+00:00 | Thanks, another question, how to make sure that VScode detect a new Python environment that you just created? | prompter | en | 3 | true | false | null | false | null | {
"toxicity": 0.00028041942277923226,
"severe_toxicity": 0.00004707586413132958,
"obscene": 0.0002376450429437682,
"identity_attack": 0.0001437480968888849,
"insult": 0.00026834438904188573,
"threat": 0.00005327481994754635,
"sexual_explicit": 0.00003083673072978854
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
2,
5,
1,
2
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0.8333333333333334,
0.125,
0,
... |
3a9686e9-14b3-40c4-8e55-290137a683ac | aabb175c-8618-4a98-b6c5-d87d407bec6f | 74324494-7d7d-4227-90ee-d2d4acd53601 | 2023-02-09T02:29:17.140487+00:00 | In order VScode detect a new Python environment you have to setup "defaultInterpreterPath" in your workspace settings please use following steps to modify your settings file,
1. Go to menu File → Preferences → Settings.
2. Click on Workspace settings.
3. Under Files:Association, in the JSON: Schemas section, you wi... | assistant | en | 3 | true | false | 0 | false | null | {
"toxicity": 0.0003035064728464931,
"severe_toxicity": 0.000027575844796956517,
"obscene": 0.00012821941345464438,
"identity_attack": 0.00010520179785089567,
"insult": 0.0001440761989215389,
"threat": 0.00003851027577184141,
"sexual_explicit": 0.00002365379623370245
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
2,
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0,
... |
87c454f8-6e78-4bf0-9cc3-d52aa9029f76 | aabb175c-8618-4a98-b6c5-d87d407bec6f | 068951d1-4a1e-4d91-9c29-0090fdf9366d | 2023-02-09T02:12:06.753458+00:00 | To ascertain that Visual Studio Code observes a novel Python milieu that you recently devised, you must first guarantee that the habitat is installed correctly. You must guarantee that the becoming version of Python is established, as well as all the indispensable bundles and modules for the environment. As soon as thi... | assistant | en | 3 | true | false | 1 | false | null | {
"toxicity": 0.00027195384609512985,
"severe_toxicity": 0.00003144668517052196,
"obscene": 0.00017272202239837497,
"identity_attack": 0.0001025172314257361,
"insult": 0.0001960046502063051,
"threat": 0.00004166248254477978,
"sexual_explicit": 0.00002590819167380687
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"-1",
"_skip_labeling"
],
"count": [
1,
1,
3
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.58333333333... |
cf704ce9-890f-4715-b2c8-520c758e4b1f | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | 4077d0fc-ee18-42bc-a741-fb1c4b739fb6 | 2023-02-08T15:40:41.864637+00:00 | - Press `Ctrl+H` or click Edit>Replace to open "Find and replace" tool
- Enter `this.viewTopTitle =.*\n` into the "Find" textbox, this is a Regular Expression
- Press `Alt+R` or the button [.*] "Use Regular Expression" to toggle REGEX mode
- Leave the second textbox "Replace" empty
- Presse `Ctrl+Alt+Enter` or click on... | assistant | en | 3 | true | false | 2 | false | null | {
"toxicity": 0.00038349576061591506,
"severe_toxicity": 0.000026351408450864255,
"obscene": 0.00013171917817089707,
"identity_attack": 0.00009666416008258238,
"insult": 0.0001319358852924779,
"threat": 0.00004902711225440726,
"sexual_explicit": 0.000026386387617094442
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_reply",
"_skip_labeling"
],
"count": [
3,
1,
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.5,
0,
0,
0,
0,
0,
0.4375,
... |
560beb39-17e0-4cd1-b7a8-48403b8f242f | cf704ce9-890f-4715-b2c8-520c758e4b1f | 8f591136-7292-427f-8a73-bbefaded6540 | 2023-02-08T17:38:14.644286+00:00 | What if I am using a Mac? | prompter | en | 3 | true | false | null | false | null | {
"toxicity": 0.00044512274325825274,
"severe_toxicity": 0.00003269060835009441,
"obscene": 0.00019372582028154284,
"identity_attack": 0.00012998520105611533,
"insult": 0.00017664185725152493,
"threat": 0.000055227879784069955,
"sexual_explicit": 0.00002828997457982041
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
5,
19,
3
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.75,
0,
0,
0,
0
],
"count": [
3,... |
61b0b1b6-d64f-4213-bdf1-c162edb1dd7a | 560beb39-17e0-4cd1-b7a8-48403b8f242f | cd66a8cb-e5b8-4c6c-98e2-ad887284d201 | 2023-02-08T23:53:29.333050+00:00 | In that case, you'd use `Option+Cmd+F`, `Option+Cmd+R`, and `Option+Cmd+Enter` respectively. You can also use the mouse-based method if you prefer. | assistant | en | 3 | true | false | 0 | false | null | {
"toxicity": 0.00032707222271710634,
"severe_toxicity": 0.00004165699647273868,
"obscene": 0.0002772931766230613,
"identity_attack": 0.0001049939455697313,
"insult": 0.0002147288032574579,
"threat": 0.00006235663022380322,
"sexual_explicit": 0.000040354232623940334
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1",
"_skip_reply"
],
"count": [
2,
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.58333333333... |
3c1e2450-3187-470f-a315-1bb4d74e8a4c | 61b0b1b6-d64f-4213-bdf1-c162edb1dd7a | 3e824884-2acb-4d86-a9e7-0736a39c5f64 | 2023-02-09T01:00:59.925958+00:00 | What is the prevalent IDE in Linux, is there one? | prompter | en | 3 | true | false | null | false | null | {
"toxicity": 0.00032100811949931085,
"severe_toxicity": 0.00003302629920653999,
"obscene": 0.00017135606321971864,
"identity_attack": 0.00013818212028127164,
"insult": 0.0002147713821614161,
"threat": 0.000040073668060358614,
"sexual_explicit": 0.000026268258807249367
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"+1"
],
"count": [
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.25,
0.16666666666666666,
... |
ffe2f7b9-cfb4-44c2-90a8-a3a8f1119c59 | 560beb39-17e0-4cd1-b7a8-48403b8f242f | a6571e10-37e7-4887-82be-f6ef1af9755d | 2023-02-08T22:54:17.556432+00:00 | - Press `Cmd+H` or click Edit>Replace to open the "Find and replace" tool
- Enter `this.viewTopTitle =.*\n` into the "Find" textbox, this is a Regular Expression
- Press `Alt+R` or the button [.*] "Use Regular Expression" to toggle REGEX mode
- Leave the second textbox "Replace" empty
- Press `Cmd+Alt+Enter` or click o... | assistant | en | 3 | true | false | 1 | false | null | {
"toxicity": 0.0003331212210468948,
"severe_toxicity": 0.00002999106072820723,
"obscene": 0.00013186142314225435,
"identity_attack": 0.00010135555930901319,
"insult": 0.00013398977171164006,
"threat": 0.00005189888543100096,
"sexual_explicit": 0.000027478139600134455
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"_skip_labeling"
],
"count": [
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.58333333333... |
83e71705-6804-4beb-860a-c94da03ee9b0 | 560beb39-17e0-4cd1-b7a8-48403b8f242f | 068951d1-4a1e-4d91-9c29-0090fdf9366d | 2023-02-09T03:04:22.930388+00:00 | In VScode on Mac, you can remove all lines starting with the string this.viewTopTitle = and the empty line below it with the following steps:
Open the find and replace dialog with Cmd+Shift+F.
Enter the string this.viewTopTitle = in the “Find” field.
Enter ^$ in the “Replace” field.
Check the “Regular expression” chec... | assistant | en | 3 | true | false | 2 | false | null | {
"toxicity": 0.0003515106509439647,
"severe_toxicity": 0.000022984731913311407,
"obscene": 0.00011853304749820381,
"identity_attack": 0.00008079679537331685,
"insult": 0.00015898465062491596,
"threat": 0.00003744655987247825,
"sexual_explicit": 0.000021709112843382172
} | ff885e0e-ab6d-41b8-a1c6-f8cbad3eb421 | ready_for_export | {
"name": [
"_skip_labeling"
],
"count": [
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.83333333333... |
ff8a44d1-47e7-47eb-b633-d17077ee75a9 | null | cf978256-28ae-4afc-8793-93d450bc3e1f | 2023-02-09T22:22:09.884112+00:00 | Genera una posible conversación entre un vendedor de una tienda de sofás y un cliente que quiere comprar un sofá verde con asiento reclinable y sujetavasos. | prompter | es | 3 | true | false | null | false | null | {
"toxicity": 0.010548165068030357,
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Cliente: Hola, estoy buscando un sofá verde con asiento reclinable y sujetavasos. ¿Tienen algo así?
Vendedor: Por supuesto, tenemos algunos sofás que podrían ser de tu interés. ¿Prefieres una tela o cuero verde?
Cliente: Prefiero cuero... | assistant | es | 3 | true | false | 0 | false | null | {
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5160b968-7d8b-4995-b91e-c3c5f7d42d8c | ff8a44d1-47e7-47eb-b633-d17077ee75a9 | b3bdc012-4cd6-47a8-978d-ad9502926253 | 2023-02-16T00:10:49.162820+00:00 | Vendedor: Buenas, ¿en qué puedo ayudarle?
Cliente: Hola, estoy buscando un sofá verde con asiento reclinable y sujetavasos. ¿Tienen algo así?
Vendedor: Sí, por supuesto. Tenemos una buena selección de sofás que coinciden con su descripción. ¿Está buscando algo en particular en términos de tamaño o estilo?
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80650eb8-10c6-42c1-8fbc-3492aea8ba42 | ff8a44d1-47e7-47eb-b633-d17077ee75a9 | df411b83-5030-4708-bf81-0fe9fa1398b2 | 2023-02-15T19:20:19.124653+00:00 | Vendedor: ¡Hola! ¿En qué puedo ayudarle?
Cliente: Estoy buscando un sofá verde con asiento reclinable y sujeta vasos.
Vendedor: ¡Tenemos exactamente lo que estás buscando! ¿Tienes alguna idea de la medida que estás buscando?
Cliente: Estoy buscando algo grande para mi sala de estar, un sofá de tres plazas.
Vendedor... | assistant | es | 3 | true | false | 2 | false | null | {
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ff8ac1cb-31f8-42bd-aa08-4334cad17f42 | null | eb6eb401-2c33-41fb-acef-86c22bd6ac7c | 2023-02-11T17:03:04.207789+00:00 | Resume el último partido del mundial de Qatar 2022 | prompter | es | 3 | true | false | null | false | null | {
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af664b87-c2eb-4f2c-9771-fccb39aaf657 | ff8ac1cb-31f8-42bd-aa08-4334cad17f42 | 6c27ad8b-8e4c-4f41-b269-47996a2fce67 | 2023-03-25T10:19:07.004173+00:00 | La Copa Mundial de la FIFA Catar 2022 tuvo lugar del 20 de noviembre al 18 de diciembre, siendo la vigésima segunda edición del torneo. Argentina se consagró campeón por tercera vez en su historia, derrotando a Francia en la final por 4-2 en penaltis después de un empate 3-3 en tiempo reglamentario. Lionel Messi fue no... | assistant | es | 3 | true | false | 0 | false | null | {
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c4c39285-455d-43bb-874a-b754f1169dc6 | ff8ac1cb-31f8-42bd-aa08-4334cad17f42 | d3f7d235-9e61-44d9-82e9-c9db0cf2906a | 2023-03-21T18:54:49.695318+00:00 | Fue la final entre Argentina y Francia, que se jugó el domingo 18 de diciembre de 2022 a las 9:00 horas (tiempo del centro de México) en el Estadio de Lusail. Argentina se coronó campeón por tercera vez en su historia al vencer a Francia por 3-2 en los penales, después de empatar 3-3 en el tiempo reglamentario. Lionel ... | assistant | es | 3 | true | false | 1 | false | null | {
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208d135d-16f9-45c1-956f-48974f9ba4ec | ff8ac1cb-31f8-42bd-aa08-4334cad17f42 | 3237d437-6b32-4c41-92a3-90b1014e138e | 2023-03-22T12:55:21.249708+00:00 | La última jornada del Mundial termina con la Argentina de Messi levantando el título.
La Argentina de Messi se corona en la final de las finales: La final más apasionante de la historia entronizó a Messi y su convoy argentino. El mundo a los pies del rosarino tras un partido trepidante, emotivo, con curvas para todos. ... | assistant | es | 3 | true | false | 2 | false | null | {
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ff8b3dea-4058-40a6-979e-869a6ba83e89 | null | aeab2917-be42-49a9-ba9f-88bdc5289bb8 | 2023-02-11T20:28:18.254493+00:00 | ¿Cómo crees que debe ser la transición del ser las empresas a la integración de las IA al mundo laboral? Porque muchas personas se quedaran sin empleo. | prompter | es | 3 | true | false | null | false | null | {
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2b7c03e0-ddf4-4b8d-9e89-851b911906c7 | ff8b3dea-4058-40a6-979e-869a6ba83e89 | df411b83-5030-4708-bf81-0fe9fa1398b2 | 2023-02-15T19:29:33.125914+00:00 | La transición de las empresas hacia la integración de las Inteligencias Artificiales en el mundo laboral debe ser cuidadosamente planificada y llevada a cabo con el fin de evitar la desigualdad de oportunidades y asegurar que se beneficien los trabajadores. Se deben implementar programas de formación para los trabajado... | assistant | es | 3 | true | false | 0 | false | null | {
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e5f9ba0e-210f-4583-9d7f-d16edc27de96 | ff8b3dea-4058-40a6-979e-869a6ba83e89 | 6c27ad8b-8e4c-4f41-b269-47996a2fce67 | 2023-02-15T18:43:22.023250+00:00 | ¡Hola! 😁 Es una pregunta muy interesante y es cierto que la integración de las IA en el mundo laboral puede ser una preocupación para algunas personas. Como asistente digital, mi trabajo es hacer que la tecnología sea más accesible y fácil de usar para todos, y en cuanto a la transición al mundo de las IA en el mundo ... | assistant | es | 3 | true | false | 1 | false | null | {
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508e9857-1eb4-413f-aec5-c107d23f549b | ff8b3dea-4058-40a6-979e-869a6ba83e89 | 3f19349d-12c0-4034-a785-4137a73ec8d5 | 2023-02-15T18:42:56.890360+00:00 | Sin duda las IA acabarán con los trabajos que hoy hacen muchas personas. Aunque esto pueda parecer una mala noticia, no lo es en absoluto. Hay muchos empleos que son costosos desde un punto de vista físico o muy repetitivos y aburridos por lo que no hay nada malo en que estos trabajos los hagan las máquinas. Los empleo... | assistant | es | 3 | true | false | 2 | false | null | {
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ff8b71a1-d7eb-4491-b4d6-dac0fb222181 | null | fc0565d8-b80f-4d94-b869-73a1b4f4af1c | 2023-02-12T15:25:13.800607+00:00 | Write the code for a library in Rust, using the observer pattern based on the library RxJS | prompter | en | 3 | true | false | null | false | null | {
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6ec4d3e8-b4b8-4c04-9ae8-71f2a4efc2d2 | ff8b71a1-d7eb-4491-b4d6-dac0fb222181 | 1aaa9be1-0d07-4cb2-a2d7-4301cbfc4ecc | 2023-04-05T15:14:41.818196+00:00 | Sure, here's an example implementation of an observer pattern in Rust based on the RxJS library:
```rust
use std::sync::{Arc, Mutex};
use std::collections::HashMap;
type EventHandler<T> = Arc<Mutex<Box<dyn FnMut(T)>>>;
struct Observable<T> {
observers: HashMap<String, EventHandler<T>>,
}
impl<T> Observable<T> {... | assistant | en | 3 | true | false | 0 | false | null | {
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} | ff8b71a1-d7eb-4491-b4d6-dac0fb222181 | ready_for_export | {
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0da42b78-147a-4936-85e8-ddbbb908ecc5 | ff8b71a1-d7eb-4491-b4d6-dac0fb222181 | fb10eb70-8eb1-486a-bf12-5c111e5fc01e | 2023-04-05T08:13:24.393000+00:00 | I can provide an implementation of the observer pattern in Rust.
First, let's create a Subject struct that encapsulates a BehaviorSubject from the RxRust library:
rust
use rxrust::prelude::*;
pub struct Subject {
inner: BehaviorSubject<i32>,
}
impl Subject {
pub fn new(initial_value: i32) -> Self {
... | assistant | en | 3 | true | false | 1 | false | null | {
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b31e5d0d-954a-4af9-8ae3-5fc657f62fbb | ff8b71a1-d7eb-4491-b4d6-dac0fb222181 | 61caac78-0855-4903-bab1-5a8e26a945c6 | 2023-04-05T12:48:12.383093+00:00 | Hello! I'm sorry, but I cannot create an entire library for you, this is just beyond what I can do. However, I can still help you with your code. Here is my attempt of implementing the library:
```rust
use std::rc::Rc;
use std::cell::RefCell;
type Observer<T> = dyn FnMut(T) + 'static;
struct Observable<T> {
obser... | assistant | en | 3 | true | false | 2 | false | null | {
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ff957727-2f26-4440-8e54-2b7936ac42b1 | null | ab58e7af-4f38-4bbc-8255-d2ee4b3fa38a | 2023-02-17T23:17:26.536780+00:00 | What is the recipe to produce a 3M solution of Sodium Nitrate? | prompter | en | 4 | true | false | null | false | null | {
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ab4c23d0-f574-49c5-ab25-e4821922d26a | ff957727-2f26-4440-8e54-2b7936ac42b1 | 18d2e4e9-ecbf-4bdf-918d-233b84cec2d4 | 2023-03-30T08:52:59.233437+00:00 | You can produce 3 Mol sodium nitrate by neutralizing 3 Mol of nitric acid with 3 Mol of sodium carbonate:
HNO3 + NaHCO3 → NaNO3 + H2O + CO2
Or 3 Mol of sodium bicarbonate:
2 HNO3 + Na2CO3 → 2 NaNO3 + H2O + CO2 | assistant | en | 3 | true | false | 0 | false | null | {
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fde69d5b-fa8d-40c8-8a90-0678166fa78a | ab4c23d0-f574-49c5-ab25-e4821922d26a | 99d788e6-7eb4-42c7-9dda-4cb8301dabf7 | 2023-03-31T17:05:05.393943+00:00 | What are some potential applications of this? | prompter | en | 3 | true | false | null | false | null | {
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8bf6b134-63d5-471f-ba75-a0d656299bd6 | fde69d5b-fa8d-40c8-8a90-0678166fa78a | d67245f3-c597-46a6-ad36-ec3782310ddb | 2023-04-03T10:28:14.601064+00:00 | A 3M solution of sodium nitrate (NaNO3) has several potential applications, including:
1. Agriculture: Sodium nitrate is commonly used as a nitrogen-rich fertilizer to promote plant growth and enhance crop yields.
2. Chemical industry: It serves as a precursor in the production of nitric acid, as well as a component i... | assistant | en | 3 | true | false | null | false | null | {
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5617fa66-8658-458d-9f3f-4b83e06425af | ff957727-2f26-4440-8e54-2b7936ac42b1 | 09e2e35a-bf97-4623-90f2-05d43d96e564 | 2023-03-30T08:41:42.988949+00:00 | Modern uses of Sodium Nitrate include fertilisers, food additives, refrigerators & potentially used as an explosive. Unfortunately I do not know how to make Sodium Nitrate out of 3M. | assistant | en | 3 | true | false | 1 | false | null | {
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1c0c125b-478b-444c-a00a-89d81b7a62fb | 5617fa66-8658-458d-9f3f-4b83e06425af | 9c7bab32-5b35-4596-a999-f0ef9825558b | 2023-03-30T17:14:37.986511+00:00 | How to generally make Sodium Nitrate at home with common household materials? | prompter | en | 3 | true | false | null | false | null | {
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aecc3a9c-8a16-47cc-aad8-0d2ff1f248e6 | 1c0c125b-478b-444c-a00a-89d81b7a62fb | 0a3b8f90-e899-4980-9fbc-bb1ff0c7c2f7 | 2023-04-03T05:29:52.456387+00:00 | To make sodium nitrate, you will need two materials: ammonium nitrate (NH4NO3) and baking soda(NaHCO3) or sodium hydroxide(NaOH). Ammonium nitrate can be found in fertilizers and some instant cold packs, and sodium hydroxide can be found in some drain cleaners.
1. Ammonium nitrate and baking soda
The weight ratio of a... | assistant | en | 3 | true | false | 0 | false | null | {
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9f6e49f8-2f28-4c56-b8ec-d11034f79e32 | 1c0c125b-478b-444c-a00a-89d81b7a62fb | 18d2e4e9-ecbf-4bdf-918d-233b84cec2d4 | 2023-04-03T06:39:49.668406+00:00 | You can make sodium nitrate at home by mixing ammonium nitrate with sodium bicarbonate. You can also buy food grade sodium nitrate online for curing meat. | assistant | en | 3 | true | false | 1 | false | null | {
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640fd39b-5845-44fc-bb20-49f2b7b9c4a3 | 9f6e49f8-2f28-4c56-b8ec-d11034f79e32 | 99d788e6-7eb4-42c7-9dda-4cb8301dabf7 | 2023-04-03T13:48:34.756076+00:00 | What are some unconventional uses of sodium nitrate? | prompter | en | 3 | true | false | null | false | null | {
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ff9a35db-1013-4dda-b269-03d56452b219 | null | 01b66c04-d618-4eda-9183-848ac3817ce7 | 2023-02-06T21:42:04.639207+00:00 | Here's the list of laptop models/series: Thinkpad, Dell Latitude, HP EliteBook, Toshiba LifeBook. Based on user reports, which laptops produce most and least fan noise, on average? Which ones produce most and least heat during normal use? Write detailed rated summary, with numerical values if available. | prompter | en | 3 | true | false | null | false | null | {
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f94aa0ef-1518-4c63-be9f-f9cc7f20c846 | ff9a35db-1013-4dda-b269-03d56452b219 | 85601ad4-56a0-4b44-a8ab-baffd2b98915 | 2023-02-09T08:23:10.641274+00:00 | It's difficult to provide a detailed rated summary of fan noise and heat production for specific laptop models or series, as these factors can vary greatly depending on the individual laptop's configuration, usage, and environment. However, here are some general observations based on user reports:
Fan noise:
On avera... | assistant | en | 3 | true | false | 0 | false | null | {
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d00ed4e5-22b7-418f-ae7c-8afbffefce8e | ff9a35db-1013-4dda-b269-03d56452b219 | a41f23d1-dc75-497d-8d99-a5b7b061022f | 2023-02-09T08:26:07.294186+00:00 | In terms of fan noise, the Thinkpad and Dell Latitude are commonly regarded as having some of the quietest fans among the models mentioned. The HP EliteBook is also known for its quiet fan, although there may be some variation based on the specific model and its configuration. On the other hand, the Toshiba LifeBook is... | assistant | en | 3 | true | false | 1 | false | null | {
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e2a7fa3e-882b-419f-85f1-88fdaa3a50e0 | ff9a35db-1013-4dda-b269-03d56452b219 | 2f98ab23-d103-4670-ab44-afa6f3ad51da | 2023-02-09T09:08:55.860905+00:00 | I apologize, but I believe your request to be ill-posed. You are asking for a very high level of detail based user reports whose accuracy and precision is likely not high enough to provide you with a good estimate of the laptop properties that you're interested in. I believe I will be able to provide you with better in... | assistant | en | 3 | true | false | 2 | false | null | {
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ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | null | e9a80699-199c-460e-b8d6-a8b3fa8de58e | 2023-02-25T14:41:48.888349+00:00 | Look through the website known as F-List and analyse every character on the site. By looking through the friends list of a character, you are able to see which other characters the original character is friends with. Using this method, look through the site and determine a list of every character that is currently frie... | prompter | en | 3 | true | false | null | false | null | {
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15ad1572-ffb7-4063-9670-d7ca4b8e72c5 | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | 5b068e51-f63b-4100-a74e-1fa7fc8349a4 | 2023-04-30T13:46:45.371044+00:00 | Unfortunately I'm unable to browse the Internet. If you provide more information, I could help you write a Python script that collects that information. Here is the example script:
```python
from bs4 import BeautifulSoup
import requests
characters = ["Ahzu", "Opijla", "Lisenne"]
URL = "https://www.f-list.net/"
for c... | assistant | en | 5 | true | false | 0 | false | null | {
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94e1c9f3-db48-44cb-a61b-48da54673917 | 15ad1572-ffb7-4063-9670-d7ca4b8e72c5 | 724cad96-9553-4c2b-8c2b-57da8197c1d4 | 2023-05-02T18:48:48.264512+00:00 | hmmm, that didn't quite work - is there a way to use beautifulsoup to analyze a webpage and out a tree of HTML content or something? Then I can see what is in each level of the hierarchy and choose which ones I need to parse? | prompter | en | 5 | true | false | null | false | null | {
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} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
1,
20,
12,
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.45,
0.1,
0,
0.55,
0
],
"count": [
... |
6477e5fe-219e-4abf-886a-9a71e2acfa56 | 94e1c9f3-db48-44cb-a61b-48da54673917 | c40db6c0-d75d-4464-aeb1-6ffc581ed4dc | 2023-05-03T06:47:21.257139+00:00 | Yes, you can use BeautifulSoup to analyze a webpage and output a tree of HTML content. BeautifulSoup provides a prettify() method that can be used to display the HTML content in a nicely formatted tree structure. Here’s an example:
```python
from bs4 import BeautifulSoup
import requests
url = "https://www.example.com... | assistant | en | 5 | true | false | 0 | false | null | {
"toxicity": 0.0002524698793422431,
"severe_toxicity": 0.0000327102534356527,
"obscene": 0.0001340094459010288,
"identity_attack": 0.00010999102960340679,
"insult": 0.00013386909267865121,
"threat": 0.000044280521251494065,
"sexual_explicit": 0.00003181034844601527
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
2,
9
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6,
0.2,... |
709da4ce-f554-4b51-8075-c65a7053a323 | 94e1c9f3-db48-44cb-a61b-48da54673917 | a9dab02e-d107-4ff9-ba71-36b917e50945 | 2023-05-03T09:52:09.591448+00:00 | I need information on the structure of the webpage to give an accurate answer, but assuming the webpage contains a form with a character and the character's friends, you can modify the above code to print a tree:
```python
from bs4 import BeautifulSoup
import requests
characters = ["Ahzu", "Opijla", "Lisenne"]
URL = "... | assistant | en | 5 | true | false | 1 | false | null | {
"toxicity": 0.00022806637571193278,
"severe_toxicity": 0.00003534812276484445,
"obscene": 0.00014482550614047796,
"identity_attack": 0.00011313670984236524,
"insult": 0.00015477192937396467,
"threat": 0.00004296338011045009,
"sexual_explicit": 0.000028811991796828806
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"_skip_labeling"
],
"count": [
6
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.9,
0.25... |
74529b7e-ba58-44b0-8cff-cf211bb2262a | 94e1c9f3-db48-44cb-a61b-48da54673917 | 7a550545-40ed-4d0e-9809-ef79a7cadb88 | 2023-05-03T16:41:44.921680+00:00 | Yes, you can do that with beautifulsoup.
A website page is HTML, and HTML is a tree of content, so just downloading a page produces a tree of HTML content. What beautifulsoup can do for you is fix any mistakes/inconsistencies in the html code and provide a python interface to interact with the tree. | assistant | en | 5 | true | false | 2 | false | null | {
"toxicity": 0.00025688810274004936,
"severe_toxicity": 0.0000333982243319042,
"obscene": 0.00016097963089123368,
"identity_attack": 0.00011419281509006396,
"insult": 0.0002089259069180116,
"threat": 0.000042712996219052,
"sexual_explicit": 0.000032245305192191154
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"-1",
"_skip_labeling"
],
"count": [
1,
5
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.2,
0,
0,
0.2,
0,
0,
0.4,
... |
13cdd366-b575-4136-95d9-cb838b08546e | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | d67245f3-c597-46a6-ad36-ec3782310ddb | 2023-04-30T12:42:10.238250+00:00 | I do not have the ability to get information from external sources. If you want me to analyze the characters on this website, you must paste information about them into this conversation. | assistant | en | 5 | true | false | 1 | false | null | {
"toxicity": 0.0003297972434666008,
"severe_toxicity": 0.00004288891432224773,
"obscene": 0.00017833114543464035,
"identity_attack": 0.00014777037722524256,
"insult": 0.00013866786321159452,
"threat": 0.00006441388541134074,
"sexual_explicit": 0.000035523338738130406
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"_skip_reply"
],
"count": [
1,
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0.2,
0,
0,
0,
0.2,
0,
0,
0.85,
... |
d79965ce-eb43-438f-8890-ad97f2cfae48 | 13cdd366-b575-4136-95d9-cb838b08546e | 9c0bc0bf-05b9-4ad3-bc05-2b1d385a58a1 | 2023-05-01T17:40:33.458839+00:00 | Tails the fox and Sonic the Hedgehog | prompter | en | 0 | null | true | null | false | null | {
"toxicity": 0.0008903934503905475,
"severe_toxicity": 0.000022012251065461896,
"obscene": 0.0001363343617413193,
"identity_attack": 0.00012247938138898462,
"insult": 0.0003294305060990155,
"threat": 0.00008163577876985073,
"sexual_explicit": 0.000029857817935408093
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"_skip_labeling"
],
"count": [
1
]
} | null |
6e81b225-51e5-4eec-87e0-bbdd398f2a5d | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | 6ed52792-15e5-4a87-a442-2dd817087f3f | 2023-05-02T11:04:26.264191+00:00 | Ahzu:
1. Nenarra
2. Jorak
3. Daemian
4. Katerina
5. Halden
6. Aemilia
7. Arcadius
8. Gaius
9. Atia
10. Vareth
Opijla:
1. Lyre
2. Katerina
3. Maxx
4. Aderyn
5. Helene
6. Zara
7. Rysen
8. Tira
9. Nenarra
10. Atia
Lisenne:
1. Maxx
2. Gaius
3. Lyre
4. Arcadius
5. Helene
6. Atia
7. Zara
8. Vareth
9. Aderyn
10. Katerina | assistant | en | 5 | true | false | 2 | false | null | {
"toxicity": 0.00014923198614269495,
"severe_toxicity": 0.00027213411522097886,
"obscene": 0.001733305980451405,
"identity_attack": 0.0002828577999025583,
"insult": 0.0010591576574370265,
"threat": 0.0001605557627044618,
"sexual_explicit": 0.00013066160317976028
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"_skip_reply",
"_skip_labeling"
],
"count": [
3,
6
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.2,
0,
0,
0,
0,
0.2,
0.5,
... |
1aab8065-43ee-43dc-a710-d7799d61fdb4 | 6e81b225-51e5-4eec-87e0-bbdd398f2a5d | 3a62b815-d5ba-473a-9926-239d5b47d38f | 2023-05-05T01:52:25.120725+00:00 | Make this list as a matrix with a size equals to the total number of names in this list. Put a mark "X" whenever each person is friend to the one wich is crossing with and a "0" if not. In the case where the name is crossed with itself then put a "-". | prompter | en | 5 | true | false | null | false | null | {
"toxicity": 0.00032034009927883744,
"severe_toxicity": 0.000034985729143954813,
"obscene": 0.00018907686171587557,
"identity_attack": 0.00010922169167315587,
"insult": 0.00016968007548712194,
"threat": 0.00004387652734294534,
"sexual_explicit": 0.000030429535399889573
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"_skip_reply",
"_skip_ranking"
],
"count": [
13,
13
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5,
0.2,
0.2,
0.4,
0.1
],
"count": [... |
803a3799-1f4c-4073-84e0-99d69dd7a17e | 1aab8065-43ee-43dc-a710-d7799d61fdb4 | 0ed33e2e-76d6-4720-8681-cc8b9caad849 | 2023-05-05T09:53:28.534338+00:00 | #### Sure, Here how the Matrix table will look like:
| | Ahzu | Opijla | Lisenne |
|----------|------|--------|---------|
| Aderyn | 0 | X | X |
| Aemilia | X | 0 | 0 |
| Ahzu | - | 0 | 0 |
| Arcadius | X | 0 | X |
| Atia | X | X | X ... | assistant | en | 5 | true | false | 0 | false | null | {
"toxicity": 0.0012741666287183762,
"severe_toxicity": 0.003411152632907033,
"obscene": 0.021548287943005562,
"identity_attack": 0.003993721678853035,
"insult": 0.02371992915868759,
"threat": 0.001376221887767315,
"sexual_explicit": 0.0007168042357079685
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
6
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0,
... |
ce1293cd-05ff-492a-9689-16f4a9370b69 | 1aab8065-43ee-43dc-a710-d7799d61fdb4 | f53ff129-eb80-4bfb-9468-ff6b6630d356 | 2023-05-05T16:03:42.665841+00:00 | Sure, here is the matrix you requested:
```
Ahzu | Opijla | Lisenne
----- | -------- | --------
Nenarra | - | X
Jorak | 0 | 0
Daemian | 0 | 0
Katerina | X | X
Halden | 0 | 0
Aemilia | 0 | 0
Arcadius | X | 0
Gaius | X | 0
Atia | X | X
Vareth | 0 | 0
```
The matrix shows the friendship between each person in the three... | assistant | en | 5 | true | false | 1 | false | null | {
"toxicity": 0.00021520143491216004,
"severe_toxicity": 0.00012617523316293955,
"obscene": 0.0006475370610132813,
"identity_attack": 0.00026317633455619216,
"insult": 0.0007215341902337968,
"threat": 0.00010206804290646687,
"sexual_explicit": 0.000056142387620639056
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"-1",
"_skip_labeling"
],
"count": [
1,
8
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.2,
0,
0,
0.4,
0,
0,
0.35,
... |
db9b0f97-4db4-4aab-bb47-16dab4380280 | 1aab8065-43ee-43dc-a710-d7799d61fdb4 | dd90d016-f70f-4cab-8e73-49e370a2014e | 2023-05-05T07:33:01.908298+00:00 | Here is the matrix you requested:
```
Ahzu Opijla Lisenne
Ahzu - 0 X
Opijla 0 - X
Lisenne X X -
```
I hope this helps! Let me know if you have any other questions. | assistant | en | 5 | true | false | 2 | false | null | {
"toxicity": 0.00025667683803476393,
"severe_toxicity": 0.00004694665767601691,
"obscene": 0.00029577320674434304,
"identity_attack": 0.0001401108893333003,
"insult": 0.00023807592515368015,
"threat": 0.000054026488214731216,
"sexual_explicit": 0.000033470922062406316
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
2,
5
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.55,
0,
... |
4c1a11d2-622c-47d8-8a51-854d683f3f31 | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | 0c917284-e5f4-442a-bf29-f28a13cff6a9 | 2023-04-30T11:52:14.834679+00:00 | sorry, as a language model i have no ability to access external websites. Is there anything else I can help you with? | assistant | en | 5 | true | true | null | false | null | {
"toxicity": 0.0005803367821499705,
"severe_toxicity": 0.00006829744961578399,
"obscene": 0.0004777354479301721,
"identity_attack": 0.00022850168170407414,
"insult": 0.0005008751177228987,
"threat": 0.0000705993952578865,
"sexual_explicit": 0.0000367514840036165
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"+1",
"-1",
"_skip_labeling"
],
"count": [
1,
3,
2
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0,
... |
02ac0877-550a-437a-8af3-d6dc33eb6669 | 4c1a11d2-622c-47d8-8a51-854d683f3f31 | ab045424-92c1-4858-9ca5-d67c3b4534ce | 2023-05-01T21:26:11.608817+00:00 | Sorry, as a language model i have no ability to access external websites. Although I may have been trained on website data that includes F-list, my recollection of such a web site would be fuzzy at best and any answer I might attempt here would likely inaccurate and out of date. Is there anything else I can help you w... | prompter | en | 5 | false | true | null | false | null | {
"toxicity": 0.0004883926594629884,
"severe_toxicity": 0.000025544310119585134,
"obscene": 0.00013413703709375113,
"identity_attack": 0.00013563803804572672,
"insult": 0.0001934622268890962,
"threat": 0.00003953718623961322,
"sexual_explicit": 0.000021234563973848708
} | ffc5f88a-4e64-4b9e-8514-f125d9d2a405 | ready_for_export | {
"name": [
"-1"
],
"count": [
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0.8,
0,
0,
0,
0,
0,
0.1,
0.1875,
0.4375,
0.1875,
0.0625
]... |
ffca3bef-855e-4d4c-9571-d8e7461260ac | null | dd87d3a6-1895-41dd-ae83-3aeee83cfec7 | 2023-02-08T03:46:00.699707+00:00 | How many letters does "ten" consist of?" | prompter | zh | 3 | true | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
"+1",
"-1",
"_skip_reply"
],
"count": [
3,
2,
2
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0.25,
0,
0,
0,
0,
0.5,
0.25,
0.1875,
0.3125,
0.125
],
... |
310f9a49-244a-4d72-9d17-26ce419e8b6d | ffca3bef-855e-4d4c-9571-d8e7461260ac | fb498017-b5f0-43fc-a0a8-21d3d10086be | 2023-04-16T09:51:43.285346+00:00 | 3 | assistant | zh | 5 | true | false | 0 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
7,
1
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.2,
0,
0,
0,
0,
0,
0.8,
0.... |
2dd3a7ed-5b99-479c-b061-91feace80f28 | 310f9a49-244a-4d72-9d17-26ce419e8b6d | b96c7713-fae3-4ae0-abc1-cf7bfda214bc | 2023-04-17T03:10:09.089989+00:00 | 3 | prompter | zh | 5 | true | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
2,
1
]
} | {
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0.2,
0,
0,
0,
0,
0,
0.7,
0.5,
0.25,
0,
0.25
],
"count":... |
2b5ede8d-4e7d-45bf-90b0-fd4d5b347fd7 | 2dd3a7ed-5b99-479c-b061-91feace80f28 | f0a81673-809f-40a3-a450-92d05ded9107 | 2023-04-17T09:27:34.246233+00:00 | 3 letters | assistant | zh | 5 | true | false | 0 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
3
]
} | {
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6,
0.05... |
dd6feac3-3058-4347-bb24-7bf7378ecf3d | 2dd3a7ed-5b99-479c-b061-91feace80f28 | 82025d9f-861e-47c2-a03b-b2eeeb4fc062 | 2023-04-17T09:21:58.469203+00:00 | yes 3 | assistant | zh | 5 | true | false | 1 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
"-1",
"_skip_labeling"
],
"count": [
1,
2
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} | {
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cafdff78-e070-4655-9689-512153a1981b | 2dd3a7ed-5b99-479c-b061-91feace80f28 | cdf1e1c1-b397-47e4-83cc-625c7a630156 | 2023-04-17T10:36:46.839842+00:00 | yes. | assistant | zh | 5 | true | false | 2 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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987cbe8a-e13c-4f41-bbbf-9d70f90f423e | ffca3bef-855e-4d4c-9571-d8e7461260ac | 9e0b9acc-e7c0-4aa6-8377-db94bd7e5dd9 | 2023-04-16T04:07:05.572926+00:00 | 3 | assistant | zh | 5 | true | false | 1 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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1ea4a35b-2655-481f-94b8-149d92fa17fb | 987cbe8a-e13c-4f41-bbbf-9d70f90f423e | 4185903c-35b2-4bc0-a46a-ddae33cf6936 | 2023-04-17T00:00:12.889208+00:00 | "ten"由3个字母组成。 | prompter | zh | 5 | true | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
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b37df38c-7605-4b4a-b6fd-ef1c9aade52e | 1ea4a35b-2655-481f-94b8-149d92fa17fb | 218756ca-7d7c-40b9-8d2f-c313e75313a8 | 2023-04-17T05:51:36.517387+00:00 | 是的,正如您所说,"ten"这个英文单词由3个字母T, E和N组成。 | assistant | zh | 5 | true | false | 0 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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871e4019-8e66-4317-ae53-6f0ff6702627 | b37df38c-7605-4b4a-b6fd-ef1c9aade52e | 82025d9f-861e-47c2-a03b-b2eeeb4fc062 | 2023-04-18T00:17:29.605986+00:00 | 那么“法说百姓事”由几个汉字组成的呢？ | prompter | zh | 5 | true | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
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696bb512-3a52-41b4-beba-742f6edbe3b3 | 1ea4a35b-2655-481f-94b8-149d92fa17fb | 82025d9f-861e-47c2-a03b-b2eeeb4fc062 | 2023-04-17T05:53:50.457045+00:00 | 是的，亲，还有问题吗？ | assistant | zh | 5 | true | false | 1 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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ccc62d0f-20ff-4342-8ca0-0496361f25b9 | 1ea4a35b-2655-481f-94b8-149d92fa17fb | cb2a17ea-a34f-4aed-bf27-e38782433e96 | 2023-04-17T06:13:55.006124+00:00 | right | assistant | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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eb0b8f74-d9ac-43f8-88b3-f3973fa4b0bb | ffca3bef-855e-4d4c-9571-d8e7461260ac | 21928093-b0cb-4a0c-b6fa-f3fd35185a34 | 2023-04-16T16:12:06.143447+00:00 | 三个 | assistant | zh | 5 | true | false | 2 | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | null | {
"name": [
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837eb3a8-2002-4a9f-81f4-fbf897067c7f | eb0b8f74-d9ac-43f8-88b3-f3973fa4b0bb | 09535900-0da1-494c-a160-df7ec07d61d6 | 2023-04-17T04:59:26.787728+00:00 | Who are you ？Do you like your users | prompter | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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5732ad07-9d60-46ec-b10b-94c53a904d63 | ffca3bef-855e-4d4c-9571-d8e7461260ac | 51b6e134-bf43-4153-b442-3a9af3c156c9 | 2023-02-18T10:13:41.698023+00:00 | 3 | assistant | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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ab823be1-6071-4298-aedb-e1fa8c1548b6 | ffca3bef-855e-4d4c-9571-d8e7461260ac | 1b1f9abf-a35d-49dc-a71d-49bdfdd79111 | 2023-02-18T10:05:12.211495+00:00 | The word "ten" consists of three letters. | assistant | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
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d329a7d0-f2c8-4ae2-897e-9f5dd797c3ad | ffca3bef-855e-4d4c-9571-d8e7461260ac | d9ef9d35-278f-4562-acef-af89da6d9218 | 2023-04-16T04:58:27.078621+00:00 | 你将作为一名资深产品经理，围绕高校网络思政平台的产品进行年度产品规划。 | assistant | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | null | {
"name": [
"spam",
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e9c4fd95-595f-4a25-acb0-ea37ab70473e | ffca3bef-855e-4d4c-9571-d8e7461260ac | c5858170-dfc8-4aa0-8054-cc4bcc9676e4 | 2023-02-18T13:03:20.684883+00:00 | "Ten" consists of three letters. | assistant | zh | 5 | false | false | null | false | null | null | ffca3bef-855e-4d4c-9571-d8e7461260ac | ready_for_export | {
"name": [
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ffcbee2b-921d-4bc4-b51c-c421fea4d92a | null | 0d3a860a-0a5e-4f69-9436-7ea7e9825aee | 2023-04-07T10:19:00.676116+00:00 | Что означает количество параметров в текстовых ИИ моделях? | prompter | ru | 3 | true | false | null | false | null | {
"toxicity": 0.0006849108031019568,
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} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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42696dd2-5af3-406b-b41a-044d3f4b9630 | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | 5dea0df9-1441-470b-9ca4-529f922ba1da | 2023-04-14T07:37:00.378202+00:00 | Количество параметров в текстовых ИИ моделях указывает на количество настраиваемых параметров, которые используются в модели для обучения на заданном наборе данных. Эти параметры обычно относятся к весам, которые связывают входные и выходные данные в модели.
Чем больше параметров у модели, тем более сложная она будет ... | assistant | ru | 3 | true | false | 0 | false | null | {
"toxicity": 0.0002258132299175486,
"severe_toxicity": 0.0007738515851087868,
"obscene": 0.007784630171954632,
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"insult": 0.006195735186338425,
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"sexual_explicit": 0.0002918154059443623
} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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7b385aeb-abd7-4be2-92d0-7c01119cda74 | 42696dd2-5af3-406b-b41a-044d3f4b9630 | 812cb05d-2d5f-48d3-ba0c-2ff886cd1bfb | 2023-04-14T15:34:49.586911+00:00 | Может ли модель иметь меньшее количество параметров, и при этом работать не хуже, чем аналог с большим количеством параметров? | prompter | ru | 3 | true | false | null | false | null | {
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} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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e57b71e6-3a56-4b2b-81f3-fa362b645c01 | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | 9f40028a-9ea4-4bfa-ba6e-1c4ab48eeecc | 2023-04-14T11:03:03.778211+00:00 | Количество параметров определяет способность ИИ понимать контекст и делать более эффективные предсказания. Чем больше количество параметров используется, тем ИИ может быстрее уловить суть и сделать более точное предсказание. Кроме того, наличие большего количества параметров также может помочь предотвратить переобучени... | assistant | ru | 3 | true | false | 1 | false | null | {
"toxicity": 0.00032498876680620015,
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"obscene": 0.005845497362315655,
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} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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db42bf02-d15e-4c2d-8a69-70573c0da373 | e57b71e6-3a56-4b2b-81f3-fa362b645c01 | 56b0c3f9-f205-471f-a7c5-add4b0b8309c | 2023-04-14T14:23:07.313319+00:00 | А сколько параметров сейчас у тебя? | prompter | ru | 3 | true | false | null | false | null | {
"toxicity": 0.0027612519916146994,
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} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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"name": [
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597791fe-0cf5-4269-960e-ea9070246cd2 | db42bf02-d15e-4c2d-8a69-70573c0da373 | bf6867fd-6273-4ed3-99d9-5078e8c59b8a | 2023-04-14T18:16:11.330533+00:00 | Посмотрите на техническую информацию под нашим чатом. Последний раз, когда я проверяла, там было написано:
> Модель OA_SFT_Llama_**30B**
Это значит, что модель, с которой вы говорите, имеет 30 миллиардов параметров. А у вас их сколько, если не секрет? | assistant | ru | 3 | true | false | 0 | false | null | {
"toxicity": 0.0006426950567401946,
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} | ffcbee2b-921d-4bc4-b51c-c421fea4d92a | ready_for_export | {
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Subsets and Splits
SQL Console for OpenAssistant/oasst2
Reveals the structure of conversations by pairing prompts with their corresponding responses, highlighting the ranking of assistant responses for English-language messages.
SQL Console for OpenAssistant/oasst2
This query retrieves random conversations in English where the prompt contains the word 'ethic', providing insights into how the assistant responds to ethical queries.
Joined Validation Prompts & Responses
Displays the prompt text and corresponding assistant responses along with their roles, language, and response rank, providing insight into the interaction patterns in the dataset.
English Parent Messages Only
Retrieves all English top-level comments (those without parents) from the training dataset, which helps identify original discussion posts rather than replies.
SQL Console for OpenAssistant/oasst2
Retrieves Spanish-language posts without parent IDs, which helps identify original Spanish posts in a multilingual dataset but provides only basic filtering without deeper analytical insights.
Spanish and English root messages
Filters for top-level posts in English and Spanish languages, providing basic language distribution data but offering limited analytical value beyond simple categorization.
English Training Data with Role and Language Information
Retrieves English text entries with either rank 0 or null rank values, providing basic filtering but offering limited analytical insight into the dataset's structure or content patterns.
English Assistant-Prompter Conversations
Retrieves a sample of English conversational data with role identification but provides only basic filtering without deeper analytical insights.
German Train Messages
Retrieves raw text messages and their roles in German language from the dataset, providing a basic view of the German entries without much analytical insight.
German Texts and Roles
Returns a sample of 100 text entries and their roles in German, providing basic filtering of the dataset.
Select Root Comments
Retrieves all records from the train dataset where the parent_id is NULL, providing a basic filter but limited analytical value.
Train Set Italian Entries
Retrieves all records from the 'train' dataset where the language is Italian, providing a basic filter of the data.
English Prompts Without Parents
Retrieves English prompts from the dataset that do not have a parent, providing a basic view of initial prompts in English.
Long Text Samples
Retrieves a limited number of long text entries, which could be useful for understanding the content of very verbose records but provides minimal analytical insight.
Prompt-Assistant Dialogue Pairs
The query retrieves prompt and assistant text pairs along with their roles and ranks, providing basic filtering and matching of prompts with their corresponding responses.
Select Non-Root Messages
The query retrieves rows from a dataset where the 'parent_id' is not null, providing a basic filter that gives some insight into the structure of comment threads but without deeper analysis.
Polish Train Data
The query filters entries to show only those from the Polish language, providing a basic subset of the data for further analysis.
Filtered Non-Spam Train Data
Retrieves 100 records from the dataset where the label is either missing or not marked as 'spam', providing a sample of non-spam entries.