Datasets:
davanstrien
/
embedded-cards

Dataset card Data Studio Files
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ihaflix1/rodrigosilva
ihaflix1
2023-11-17T14:42:12Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T14:42:12Z
2023-11-17T14:41:04.000Z
2023-11-17T14:41:04
--- license: openrail ---
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null
null
null
null
null
null
null
null
null
null
null
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null
vanesa1221/llama2-unsaac
vanesa1221
2023-11-17T14:57:13Z
0
0
null
[ "size_categories:n<1K", "language:es", "license:mit", "region:us" ]
2023-11-17T14:57:13Z
2023-11-17T14:43:27.000Z
2023-11-17T14:43:27
--- license: mit language: - es size_categories: - n<1K --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed]
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null
null
null
null
null
null
null
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null
Kaue123456/GokuWendelBezerra
Kaue123456
2023-11-17T14:58:09Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T14:58:09Z
2023-11-17T14:54:44.000Z
2023-11-17T14:54:44
--- license: openrail ---
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wuzhanliai21/lioatian
wuzhanliai21
2023-11-17T14:57:50Z
0
0
null
[ "region:us" ]
2023-11-17T14:57:50Z
2023-11-17T14:57:50.000Z
2023-11-17T14:57:50
Entry not found
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null
null
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ksanjeev284/shilohdynasty
ksanjeev284
2023-11-17T15:00:56Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-17T15:00:56Z
2023-11-17T14:59:39.000Z
2023-11-17T14:59:39
--- license: mit ---
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KarunAgarwal/test
KarunAgarwal
2023-11-17T15:02:54Z
0
0
null
[ "region:us" ]
2023-11-17T15:02:54Z
2023-11-17T15:02:52.000Z
2023-11-17T15:02:52
Entry not found
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kiennguyen1703/HoChiMinhLeader
kiennguyen1703
2023-11-17T15:17:05Z
0
0
null
[ "language:en", "license:apache-2.0", "region:us" ]
2023-11-17T15:17:05Z
2023-11-17T15:04:26.000Z
2023-11-17T15:04:26
--- license: apache-2.0 language: - en ---
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null
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null
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null
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icaro23/jean23
icaro23
2023-11-17T15:09:32Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-17T15:09:32Z
2023-11-17T15:07:53.000Z
2023-11-17T15:07:53
--- license: apache-2.0 ---
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xsred/jaeyun1
xsred
2023-11-17T15:32:37Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T15:32:37Z
2023-11-17T15:30:32.000Z
2023-11-17T15:30:32
--- license: openrail ---
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PeterGraebner/LDNOOBW_V2
PeterGraebner
2023-11-24T15:00:57Z
0
0
null
[ "size_categories:10K<n<100K", "language:af", "language:az", "language:am", "language:be", "language:bg", "language:dz", "language:eu", "language:my", "language:ca", "language:cs", "language:cy", "language:hr", "language:zh", "language:da", "language:de", "language:nl", "language:el...
2023-11-24T15:00:57Z
2023-11-17T16:06:07.000Z
2023-11-17T16:06:07
--- license: cc0-1.0 language: - af - az - am - be - bg - dz - eu - my - ca - cs - cy - hr - zh - da - de - nl - el - en - eo - es - et - fa - fi - fr - gl - gd - hi - hy - hu - id - is - it - ja - ko - la - lt - lv - mi - mk - ml - ms - mt - mr - mn - 'no' - pl - pt - ro - ru - sk - sl - sm - sq - te - ta - to - tr - uk - uz - vi - yid - zu pretty_name: List of Dirty Naughty Obscene and Otherwise Bad Words V2 size_categories: - 10K<n<100K --- > Written with [StackEdit](https://stackedit.io/). > ## [List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words_V2](https://github.com/LDNOOBWV2/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words_V2#list-of-dirty-naughty-obscene-and-otherwise-bad-words_v2) This list of words is a follow-up and extension of the Shutterstock [List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words/tree/master) as that list is not maintained anymore. As there are many profanity word lists around on the web (and many not maintained) their content was crabbed and joined here together (see the source list below). As the opinion on which words should be in such lists varies between culture, language, and geographies, feel free to extend them to your needs, hopefully getting a lot of feedback. The lists need reviews from native speakers. It would be great to collect more words and even get more languages (**75** right now, with over **50k words** alltogether). The long list of English words shows that people got very creative to get around profanity filters. The best way to use these hard-coded word lists is to use them as an additional quality criterion for filtering texts like it is done in [RedPajama](https://github.com/togethercomputer/RedPajama-Data) data set or use them for ML building profanity filters. The next TODO will be to create some regular expressions for often-used spelling variations. ### Structure and Format - filename is the **iso-code** of the country - file extension is **".txt"** - **utf-8** encoded - all words are **lowercase** - one expression per line - all words contained in the English "***en.txt***" file are **excluded** in the other language files - often used words where the classification as a profane word is doubtful, there is a separate csv file - the csv-file is: [questionable_international_words.csv](questionable_international_words.csv) - separator is the comma "**,**" - **51** words for several languages (see table below) - the header line contains the iso-code of the language, a classification column (*category*), and a *remark* column - these words are **NOT** included in the language-text-files, e.g. "*.txt" - when I couldn't find a translation, the field contains the string: **<NO_TRANSLATION>** ### Languages Files Overview language | count | filename | in csv-file | remark --- | --- | --- | --- | --- [Afrikaans](data/af.txt) | 256 | af | Y| [Albanian](data/sq.txt) | 179 | sq | Y| [Algerian](data/dz.txt) | 86 | dz | N| [Amharic](data/am.txt) | 50 | am | N| [Arabic](data/ar.txt) |1248 | ar | N| [Armenian](data/hy.txt) | 106 | hy | Y| [Australian Kriol](data/rop.txt) | 16 | rop| N| [Azerbaijanian](data/az.txt) | 37 | az | N| [Basque](data/eu.txt) | 48 | eu | N| [Belorussian](data/be.txt) | 118 | be | N| [Bulgarian](data/bg.txt) | 336 | bg | Y| [Burmese](data/my.txt) | 81 | my | N| [Cambodian](data/kh.txt) | 132 | kh | N| [Catalan](data/ca.txt) | 143 | ca | Y| [Cebuano](data/ceb.txt) | 18 | ceb| N| [Chinese](data/zh.txt) |1811 | zh | Y| [Croatian](data/hr.txt) | 267 | hr | Y| [Czech](data/cs.txt) | 241 | cs | Y| [Danish](data/da.txt) | 185 | da | Y| [Dutch](data/nl.txt) |1224 | nl | Y| [English](data/en.txt) |12996| en | Y| various spelling variations, does not contain Spanish (es) words [Esperanto](data/eo.txt) | 50 | eo | N| [Estonian](data/et.txt) | 174 | et | Y| [Filipino](data/fil.txt) | 165 | fil| Y| [Finnish](data/fi.txt) | 317 | fi | Y| [French](data/fr.txt) |3708 | fr | Y| many spelling variations [Gaelic](data/gd.txt) | 88 | gd | N| [Galician](data/gl.txt) | 74 | gl | N| [German](data/de.txt) | 622 | de | Y| [Greek](data/el.txt) | 247 | el | Y| [Hebrew](data/yid.txt) | 173 | yid| N| [Hindi](data/hi.txt) | 771 | hi | Y| [Hungarian](data/hu.txt) | 296 | hu | Y| [Icelandic](data/is.txt) | 137 | is | Y| [Italian](data/it.txt) |1755 | it | Y| [Indonesian](data/id.txt) | 582 | id | Y| [Japanese](data/ja.txt) | 468 | ja | Y| [Kabyle](data/kab.txt) | 22 | kab| N| [Klingon](data/tlh.txt) | 33 | tlh| N| [Korean](data/ko.txt) |3094 | ko | Y| [Latin](data/la.txt) | 103 | la | N| [Latvian](data/lv.txt) | 198 | lv | Y| [Lithuanian](data/lt.txt) | 158 | lt | Y| [Macedonian](data/mk.txt) | 192 | mk | N| [Malay](data/ms.txt) | 201 | ms | Y| [Malayalam](data/ml.txt) | 338 | ml | Y| [Maltese](data/mt.txt) | 132 | mt | Y| [Maori](data/mi.txt) | 58 | mi | Y| [Marathi](data/mr.txt) | 95 | mr | Y| [Mongolian](data/mn.txt) | 277 | mn | N| [Norwegian](data/no.txt) | 171 | no | Y| [Persian](data/fa.txt) | 629 | fa | N| [Pictrain-Norfolk](data/pih.txt) | 14 | pih| N| [Piya-Kwonci](data/piy.txt) | 13 | piy| N| [Polish](data/pl.txt) |8971 | pl | Y| different grammatical variations [Portuguese](data/pt.txt) | 575 | pt | Y| including Brasilian [Romanian](data/ro.txt) | 290 | ro | Y| [Russian](data/ru.txt) |4948 | ru | Y| [Samoan](data/sm.txt) | 116 | sm | Y| [Serbian](data/sr.txt) | 459 | sr | Y| sr_k & sr_l in csv file [Slovak](data/sk.txt) | 586 | sk | Y| [Slovene](data/sl.txt) | 167 | sl | Y| [Spanish](data/es.txt) |1677 | es | Y| including Middle- and South American [Swedish](data/sv.txt) | 245 | sv | Y| [Tamil](data/ta.txt) | 119 | ta | N| [Telugu](data/te.txt) | 317 | te | Y| [Tetum](data/tet.txt) | 11 | tet| N| [Thai](data/th.txt) |1715 | th | Y| [Tongan](data/to.txt) | 68 | to | N| [Turkish](data/tr.txt) | 370 | tr | Y| [Ukrainian](data/uk.txt) | 205 | uk | Y| [Uzbek](data/uz.txt) | 102 | uz | N| [Vietnamese](data/vi.txt) | 790 | vi | Y| [Welsh](data/cy.txt) | 169 | cy | Y| [Zulu](data/zu.txt) | 115 | zu | N| ### Categories in *questionable_international_words.csv* The categories used are: - **cul**: cultural differences - **dm**: drugs & medicine - **his**: historical - **leg**: Legislative term - **mab**: medical, anatomic, biological term - **pol**: political - **rel**: religious - **so**: sexual orientation - **vm**: various meanings This is just an ad hoc classification where several expressions can be in different categories.
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hyuneg/BRT-imago
hyuneg
2023-11-17T16:10:13Z
0
0
null
[ "region:us" ]
2023-11-17T16:10:13Z
2023-11-17T16:09:19.000Z
2023-11-17T16:09:19
--- dataset_info: features: - name: image dtype: image - name: label dtype: image splits: - name: train num_bytes: 981599371.92 num_examples: 9116 download_size: 938272983 dataset_size: 981599371.92 configs: - config_name: default data_files: - split: train path: data/train-* ---
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vanesa1221/admision-unsaac
vanesa1221
2023-11-17T16:50:34Z
0
0
null
[ "task_categories:question-answering", "size_categories:n<1K", "language:es", "region:us" ]
2023-11-17T16:50:34Z
2023-11-17T16:34:43.000Z
2023-11-17T16:34:43
--- task_categories: - question-answering language: - es size_categories: - n<1K --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
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gradio/custom-component-gallery-backups
gradio
2023-11-29T01:22:07Z
0
2
null
[ "license:mit", "region:us" ]
2023-11-29T01:22:07Z
2023-11-17T16:39:54.000Z
2023-11-17T16:39:54
--- license: mit ---
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enzostvs/what-is-the-prompt
enzostvs
2023-11-22T17:54:40Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-22T17:54:40Z
2023-11-17T16:44:06.000Z
2023-11-17T16:44:06
--- license: mit ---
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Lipe3434/dvdaudio
Lipe3434
2023-11-19T00:05:08Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-19T00:05:08Z
2023-11-17T16:44:25.000Z
2023-11-17T16:44:25
--- license: openrail ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
ltg/nb-samtale-conversations
ltg
2023-11-18T03:17:41Z
0
0
null
[ "task_categories:conversational", "size_categories:1K<n<10K", "language:no", "language:nb", "language:nn", "license:cc0-1.0", "region:us" ]
2023-11-18T03:17:41Z
2023-11-17T16:45:46.000Z
2023-11-17T16:45:46
--- license: cc0-1.0 task_categories: - conversational language: - 'no' - nb - nn pretty_name: NB Samtale — Conversations size_categories: - 1K<n<10K --- # NB Samtale — Conversations This dataset contains extracted and cleaned conversations from the [NB Samtale corpus](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-85/). The original is a speech corpus made by the Language Bank at the National Library of Norway. The corpus contains orthographically transcribed speech from podcasts and recordings of live events.
[ -0.3148815631866455, -0.73424232006073, 0.20626409351825714, -0.2209792584180832, -0.4637954831123352, 0.17907878756523132, 0.07403415441513062, -0.5521367788314819, 1.0704445838928223, 1.1747115850448608, -0.7401270866394043, -0.2151554524898529, -0.25440430641174316, 0.11599244922399521,...
null
null
null
null
null
null
null
null
null
null
null
null
null
vanesa1221/admi-unsaac
vanesa1221
2023-11-17T16:51:24Z
0
0
null
[ "region:us" ]
2023-11-17T16:51:24Z
2023-11-17T16:51:24.000Z
2023-11-17T16:51:24
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
vanesa1221/prueba2
vanesa1221
2023-11-17T17:00:55Z
0
0
null
[ "region:us" ]
2023-11-17T17:00:55Z
2023-11-17T16:58:21.000Z
2023-11-17T16:58:21
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
furry-br/alastor
furry-br
2023-11-17T17:01:17Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T17:01:17Z
2023-11-17T17:00:59.000Z
2023-11-17T17:00:59
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
unnotigkeit/habr
unnotigkeit
2023-11-17T17:03:59Z
0
0
null
[ "region:us" ]
2023-11-17T17:03:59Z
2023-11-17T17:03:59.000Z
2023-11-17T17:03:59
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
simonbrbx/kine
simonbrbx
2023-11-17T17:07:26Z
0
0
null
[ "license:unknown", "region:us" ]
2023-11-17T17:07:26Z
2023-11-17T17:05:54.000Z
2023-11-17T17:05:54
--- license: unknown ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
rexarski/synthfin_call_intent
rexarski
2023-11-17T18:05:01Z
0
0
null
[ "region:us" ]
2023-11-17T18:05:01Z
2023-11-17T17:14:25.000Z
2023-11-17T17:14:25
--- dataset_info: features: - name: intent dtype: string - name: text dtype: string splits: - name: train num_bytes: 546919 num_examples: 365 download_size: 269091 dataset_size: 546919 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
fantasticrambo/covid-tweet-sentiment-analyzer-distilbert-data
fantasticrambo
2023-11-17T17:48:50Z
0
0
null
[ "region:us" ]
2023-11-17T17:48:50Z
2023-11-17T17:48:48.000Z
2023-11-17T17:48:48
--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels dtype: int64 splits: - name: train num_bytes: 10366704 num_examples: 7999 - name: val num_bytes: 2592000 num_examples: 2000 download_size: 514530 dataset_size: 12958704 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
Freela/leom
Freela
2023-11-17T17:57:56Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T17:57:56Z
2023-11-17T17:50:49.000Z
2023-11-17T17:50:49
--- license: openrail ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
nguyenthanhdo/belle_vi_20k
nguyenthanhdo
2023-11-17T18:07:49Z
0
0
null
[ "region:us" ]
2023-11-17T18:07:49Z
2023-11-17T18:07:47.000Z
2023-11-17T18:07:47
--- dataset_info: features: - name: input dtype: string - name: output dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 13745755 num_examples: 20000 download_size: 5694988 dataset_size: 13745755 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
nlp-vtcc/belle_vi_20k
nlp-vtcc
2023-11-17T18:08:07Z
0
0
null
[ "region:us" ]
2023-11-17T18:08:07Z
2023-11-17T18:08:05.000Z
2023-11-17T18:08:05
--- dataset_info: features: - name: input dtype: string - name: output dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 13745755 num_examples: 20000 download_size: 5694988 dataset_size: 13745755 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
misterwhisperorg/datasets2
misterwhisperorg
2023-11-17T18:17:14Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-17T18:17:14Z
2023-11-17T18:17:14.000Z
2023-11-17T18:17:14
--- license: apache-2.0 ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
davidmunechika/dreambooth-finetuning
davidmunechika
2023-11-17T18:24:06Z
0
0
null
[ "region:us" ]
2023-11-17T18:24:06Z
2023-11-17T18:23:29.000Z
2023-11-17T18:23:29
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
Freela/leombaseteste
Freela
2023-11-17T18:39:07Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T18:39:07Z
2023-11-17T18:38:19.000Z
2023-11-17T18:38:19
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
fantasticrambo/covid-tweet-sentiment-analyzer-roberta-latest-data
fantasticrambo
2023-11-17T18:41:58Z
0
0
null
[ "region:us" ]
2023-11-17T18:41:58Z
2023-11-17T18:41:54.000Z
2023-11-17T18:41:54
--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels dtype: int64 splits: - name: train num_bytes: 10366704 num_examples: 7999 - name: val num_bytes: 2592000 num_examples: 2000 download_size: 575509 dataset_size: 12958704 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
xXDeryXx/Dery
xXDeryXx
2023-11-17T19:19:43Z
0
0
null
[ "region:us" ]
2023-11-17T19:19:43Z
2023-11-17T19:13:43.000Z
2023-11-17T19:13:43
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
icaro23/jjj
icaro23
2023-11-17T19:24:17Z
0
0
null
[ "region:us" ]
2023-11-17T19:24:17Z
2023-11-17T19:22:14.000Z
2023-11-17T19:22:14
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
Samis922/haystack_squadlike_finetuning_data
Samis922
2023-11-17T19:23:38Z
0
0
null
[ "region:us" ]
2023-11-17T19:23:38Z
2023-11-17T19:23:06.000Z
2023-11-17T19:23:06
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
TheGreatP/minhavozcerto
TheGreatP
2023-11-17T19:33:13Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T19:33:13Z
2023-11-17T19:32:16.000Z
2023-11-17T19:32:16
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
Pablao0948/Maggie
Pablao0948
2023-11-17T19:55:09Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T19:55:09Z
2023-11-17T19:54:43.000Z
2023-11-17T19:54:43
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
icaro23/jeanv23
icaro23
2023-11-17T20:03:25Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-17T20:03:25Z
2023-11-17T20:02:11.000Z
2023-11-17T20:02:11
--- license: apache-2.0 ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
aronhawkins/font-examples
aronhawkins
2023-11-17T20:44:26Z
0
0
null
[ "region:us" ]
2023-11-17T20:44:26Z
2023-11-17T20:44:26.000Z
2023-11-17T20:44:26
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
Rewcifer/validation_2000_cutoff_llama-2-7b-tyellow-2k-cutoff-LR1-clean-train_2K_results_backup
Rewcifer
2023-11-17T20:52:36Z
0
0
null
[ "region:us" ]
2023-11-17T20:52:36Z
2023-11-17T20:52:34.000Z
2023-11-17T20:52:34
--- dataset_info: features: - name: labels_and_findings dtype: string - name: prompts dtype: string - name: true_findings dtype: string - name: generated_texts dtype: string splits: - name: train num_bytes: 17497952 num_examples: 2000 download_size: 4270083 dataset_size: 17497952 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "validation_2000_cutoff_llama-2-7b-tyellow-2k-cutoff-LR1-clean-train_2K_results_backup" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.3049940764904022, -0.02161349542438984, 0.1932586431503296, 0.38285353779792786, -0.5468906164169312, -0.05921906232833862, 0.43174800276756287, 0.022636450827121735, 0.6125504374504089, 0.6722338795661926, -1.0118156671524048, -0.538307249546051, -0.44913193583488464, 0.089215002954006...
null
null
null
null
null
null
null
null
null
null
null
null
null
Weyaxi/open-llm-leaderboard-results-pr
Weyaxi
2023-11-20T12:27:46Z
0
0
null
[ "size_categories:1K<n<10K", "region:us" ]
2023-11-20T12:27:46Z
2023-11-17T21:19:56.000Z
2023-11-17T21:19:56
--- size_categories: - 1K<n<10K --- # Open LLM Leaderboard Results PR Opener's Dataset 🏆 This is the dataset of [Open LLM Leaderboard Results PR Opener](https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr). 📊 This dataset contains a CSV file, which in turn includes the discussion link for the related repository. ## Tool Link 🔗 [Weyaxi/open-llm-leaderboard-results-pr](https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr)
[ -0.012218409217894077, -0.4452938437461853, 0.08941144496202469, 0.3065614402294159, -0.29008597135543823, -0.007344813086092472, -0.19232560694217682, 0.1870317906141281, 0.5132354497909546, 0.6367063522338867, -1.0385875701904297, -1.173266887664795, -0.5749605298042297, -0.0861315801739...
null
null
null
null
null
null
null
null
null
null
null
null
null
Abcdefghijklmnopqrstuvwxyz12/HoR
Abcdefghijklmnopqrstuvwxyz12
2023-11-27T21:11:03Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-27T21:11:03Z
2023-11-17T21:31:06.000Z
2023-11-17T21:31:06
--- license: apache-2.0 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Pablao0948/Kingo
Pablao0948
2023-11-17T21:34:12Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T21:34:12Z
2023-11-17T21:33:32.000Z
2023-11-17T21:33:32
--- license: openrail ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
AlignmentLab-AI/alpaca-cot
AlignmentLab-AI
2023-11-17T21:46:13Z
0
0
null
[ "region:us" ]
2023-11-17T21:46:13Z
2023-11-17T21:46:13.000Z
2023-11-17T21:46:13
Entry not found
[ -0.3227647542953491, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965083122253, 0.7915717959403992, 0.07618629932403564, 0.7746022343635559, 0.2563222348690033, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
punwaiw/DiffusionJockey
punwaiw
2023-11-17T22:31:50Z
0
0
null
[ "region:us" ]
2023-11-17T22:31:50Z
2023-11-17T21:55:52.000Z
2023-11-17T21:55:52
--- dataset_info: features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 8055672.0 num_examples: 10 download_size: 0 dataset_size: 8055672.0 --- # Dataset Card for "DiffusionJockey" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.4506039023399353, -0.5972164273262024, 0.33705154061317444, 0.32410845160484314, -0.1753876954317093, 0.11415541917085648, 0.47050896286964417, -0.16509459912776947, 1.007068157196045, 0.3445186913013458, -0.74216228723526, -0.9004316329956055, -0.863899827003479, -0.5150690078735352, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
gagan3012/CS
gagan3012
2023-11-17T22:09:14Z
0
0
null
[ "region:us" ]
2023-11-17T22:09:14Z
2023-11-17T22:07:22.000Z
2023-11-17T22:07:22
--- dataset_info: features: - name: id dtype: string - name: text dtype: string - name: answer dtype: string - name: query dtype: string - name: choices sequence: string - name: gold dtype: int64 splits: - name: test num_bytes: 396825 num_examples: 240 download_size: 126940 dataset_size: 396825 configs: - config_name: default data_files: - split: test path: data/test-* ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
Capsekai/hogans-heroes
Capsekai
2023-11-17T22:34:11Z
0
0
null
[ "task_categories:text-classification", "size_categories:1K<n<10K", "language:en", "license:creativeml-openrail-m", "art", "region:us" ]
2023-11-17T22:34:11Z
2023-11-17T22:14:57.000Z
2023-11-17T22:14:57
--- license: creativeml-openrail-m task_categories: - text-classification language: - en tags: - art pretty_name: Hogan's Heroes by Capsekai size_categories: - 1K<n<10K --- # Dataset Card for Hogans Heroes TV Caps <!-- Provide a quick summary of the dataset. --> This dataset is generally caps from Hogans Heroes. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## Dataset Details ### Dataset Description These are curated screencaps of episodes from the 1960s tv show HOGANS HEROES. Hand picked content from online sources, and capped using VLC's scene filter. - **Curated by:** [https://capsekai.tumblr.com/] ## Uses Research around text classification and preservation of old media. ### Direct Use Study of character basis, research around the artistic nature of the episode's set design. ### Out-of-Scope Use Going against local laws and regulations, onselling the dataset. ## Dataset Creation ### Curation Rationale Preservation of old media. ### Source Data Youtube & Dvd Sources #### Data Collection and Processing Collection: Unfiltered DVD / Youtube Caps. #### Personal and Sensitive Information There should be 0 personal info in here. ## Bias, Risks, and Limitations ????? - OH! Bias/Risks: Warning that this is a show that is largely based around World War 2. Like Dad's army this could contain sensitive topics and images. The jokes set within the Reccomendations are just that we feel this TV show and the caps within are fairly safe, but it IS understandable if people largely have trigger issues with WW2. ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. Risks? Copyright, DMCA, blinding adoration towards Bob Crane? UWU KLINK? Soical bias: WW2 media. ## Dataset Card Authors [https://capsekai.tumblr.com/] ## Dataset Card Contact [https://capsekai.tumblr.com/]
[ -0.6135064363479614, -0.41918087005615234, -0.07670210301876068, -0.002564056310802698, -0.3227190673351288, 0.0023567804601043463, 0.11479682475328445, 0.015671731904149055, 0.502208411693573, 0.4535970389842987, -0.8263598084449768, -0.21514363586902618, -0.7072039842605591, 0.1549059301...
null
null
null
null
null
null
null
null
null
null
null
null
null
Raspberry-ai/cos8AT60TjozU_raw_v1
Raspberry-ai
2023-11-17T23:34:30Z
0
0
null
[ "region:us" ]
2023-11-17T23:34:30Z
2023-11-17T22:22:46.000Z
2023-11-17T22:22:46
--- dataset_info: features: - name: url dtype: string - name: name dtype: string - name: color dtype: string - name: image_path dtype: string - name: brand_name dtype: string - name: overall_description dtype: string - name: style_description dtype: string - name: material_description dtype: string - name: product_category dtype: string - name: product_group_category dtype: string - name: section_name dtype: string - name: created_at dtype: string - name: image_urls dtype: string - name: images dtype: string - name: images_path sequence: string - name: source dtype: string - name: caption dtype: string - name: s3_uris sequence: string splits: - name: train num_bytes: 5034572 num_examples: 864 download_size: 1931322 dataset_size: 5034572 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "cos_raw_dataset_v1" 864 items 1. Women clothing 2. Women shoes Average image resolution: 1120 × 1690 [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.5061913132667542, -0.13003672659397125, -0.13761895895004272, 0.18460194766521454, -0.8483036756515503, -0.26655900478363037, 0.05746835470199585, -0.6954158544540405, 0.5608107447624207, 0.3469051122665405, -0.9583126306533813, -0.9306028485298157, -0.568884551525116, -0.12980125844478...
null
null
null
null
null
null
null
null
null
null
null
null
null
simple-pretraining/wikipedia_chunked
simple-pretraining
2023-11-18T00:25:58Z
0
0
null
[ "region:us" ]
2023-11-18T00:25:58Z
2023-11-17T22:35:06.000Z
2023-11-17T22:35:06
--- dataset_info: features: - name: id dtype: string - name: text dtype: string - name: chunk_id dtype: int64 splits: - name: train num_bytes: 21215289300 num_examples: 72703460 download_size: 0 dataset_size: 21215289300 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "wikipedia_chunked" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.7332468032836914, -0.5591499209403992, 0.1371636688709259, 0.20900920033454895, -0.5212380886077881, -0.05243370309472084, 0.052104055881500244, -0.29471278190612793, 1.1280512809753418, 0.42566174268722534, -0.7083085775375366, -0.5252470374107361, -0.6291453838348389, -0.1919856518507...
null
null
null
null
null
null
null
null
null
null
null
null
null
gagan3012/FSR
gagan3012
2023-11-17T22:35:29Z
0
0
null
[ "region:us" ]
2023-11-17T22:35:29Z
2023-11-17T22:35:27.000Z
2023-11-17T22:35:27
--- dataset_info: features: - name: id dtype: string - name: text dtype: string - name: answer dtype: string - name: query dtype: string - name: choices sequence: string - name: gold dtype: int64 splits: - name: test num_bytes: 5874352 num_examples: 3931 download_size: 1688819 dataset_size: 5874352 configs: - config_name: default data_files: - split: test path: data/test-* ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
dcarpintero/arXiv.cs.CL.embedv3
dcarpintero
2023-11-22T23:18:21Z
0
0
null
[ "task_categories:text-classification", "task_categories:question-answering", "size_categories:10K<n<100K", "language:en", "license:apache-2.0", "region:us" ]
2023-11-22T23:18:21Z
2023-11-17T22:44:31.000Z
2023-11-17T22:44:31
--- license: apache-2.0 task_categories: - text-classification - question-answering language: - en size_categories: - 10K<n<100K --- This dataset comprises a collection of the most recent (up to 17 November 2023) 50K arXiv papers' metadata in the computer science category: 'cs.CL' (Computation and Language). Each metadata entry includes the embeddings for the 'title' and 'summary' (abstract) of the paper, generated using [Cohere's Embed-v3](https://txt.cohere.com/introducing-embed-v3/).
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null
null
null
null
null
null
null
null
null
null
null
null
null
introspector/llama.cpp-0002
introspector
2023-11-17T22:48:48Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-17T22:48:48Z
2023-11-17T22:48:48.000Z
2023-11-17T22:48:48
--- license: mit ---
[ -0.1285335123538971, -0.1861683875322342, 0.6529128551483154, 0.49436232447624207, -0.19319400191307068, 0.23607441782951355, 0.36072009801864624, 0.05056373029947281, 0.5793656706809998, 0.7400146722793579, -0.650810182094574, -0.23784008622169495, -0.7102247476577759, -0.0478255338966846...
null
null
null
null
null
null
null
null
null
null
null
null
null
lmlab/metamathqa-plaintext-40k
lmlab
2023-11-17T23:04:31Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-17T23:04:31Z
2023-11-17T22:56:38.000Z
2023-11-17T22:56:38
--- license: mit --- [website](https://meta-math.github.io/) / [dataset source](https://huggingface.co/datasets/meta-math/MetaMathQA-40K) prompt format: ``` USER: Message BOT: Message </s> ```
[ -0.4248945415019989, -0.4216119050979614, 0.1902054101228714, 0.20817574858665466, -0.24222220480442047, 0.2625983953475952, -0.016468459740281105, 0.4408499300479889, 0.5649493336677551, 0.5067476034164429, -1.1783387660980225, -0.6358290910720825, -0.33376801013946533, 0.1935183256864547...
null
null
null
null
null
null
null
null
null
null
null
null
null
thevox/en-nb-10k
thevox
2023-11-19T13:11:20Z
0
0
null
[ "task_categories:translation", "size_categories:10K<n<100K", "language:en", "language:nb", "language:no", "license:mpl-2.0", "region:us" ]
2023-11-19T13:11:20Z
2023-11-17T22:59:26.000Z
2023-11-17T22:59:26
--- license: mpl-2.0 task_categories: - translation language: - en - nb - 'no' pretty_name: English-Norwegian Translation size_categories: - 10K<n<100K --- ## Update See the larger dataset: [en-nb-15k](https://huggingface.co/datasets/thevox/en-nb-15k) ## Methadology Used GPT-3.5 with a translation prompt to give two versions of translation in Norwegian from English - normal and "more natural". Context is also generated. ## Data Input sample format: ``` Oversett til Norsk: {text} ``` Each output sample is formatted like this: ``` Kontekst: {a, b, c} Oversettelse: {translation} Mer naturlig: {improved_translation} ``` ## Future work Dataset will be used to train LLM-based translation models based on LLama 2 and similar to try to rival DeepL and ChatGPT machine translation. ## Dataset used Original english text from: [nampdn-ai/tiny-textbooks](https://huggingface.co/datasets/nampdn-ai/tiny-textbooks) ### Author Contaxt jonaslsa@uio.no
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null
null
null
null
null
null
null
null
null
null
null
null
null
alpayariyak/synthia_openchat
alpayariyak
2023-11-17T23:02:17Z
0
1
null
[ "region:us" ]
2023-11-17T23:02:17Z
2023-11-17T23:00:28.000Z
2023-11-17T23:00:28
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
McAldo/platypus_embeddings
McAldo
2023-11-17T23:20:32Z
0
0
null
[ "region:us" ]
2023-11-17T23:20:32Z
2023-11-17T23:20:27.000Z
2023-11-17T23:20:27
--- dataset_info: features: - name: input dtype: string - name: output dtype: string - name: instruction dtype: string - name: data_source dtype: string splits: - name: train num_bytes: 30738175.902270723 num_examples: 24895 download_size: 15478591 dataset_size: 30738175.902270723 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
BuroIdentidadDigital/recibos_izziV2
BuroIdentidadDigital
2023-11-17T23:20:39Z
0
0
null
[ "license:c-uda", "region:us" ]
2023-11-17T23:20:39Z
2023-11-17T23:20:39.000Z
2023-11-17T23:20:39
--- license: c-uda ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
Lippppxy/Mama
Lippppxy
2023-11-17T23:26:06Z
0
0
null
[ "region:us" ]
2023-11-17T23:26:06Z
2023-11-17T23:26:06.000Z
2023-11-17T23:26:06
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
spasx/tobiasforge
spasx
2023-11-17T23:36:59Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-17T23:36:59Z
2023-11-17T23:36:28.000Z
2023-11-17T23:36:28
--- license: openrail ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
olanigan/common_voice_13_0_yo_pseudo_labelled
olanigan
2023-11-18T00:15:45Z
0
0
null
[ "license:cc0-1.0", "region:us" ]
2023-11-18T00:15:45Z
2023-11-18T00:15:45.000Z
2023-11-18T00:15:45
--- license: cc0-1.0 ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
Chefelipe/LUANPEREIRA
Chefelipe
2023-11-18T01:02:29Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-18T01:02:29Z
2023-11-18T01:02:03.000Z
2023-11-18T01:02:03
--- license: openrail ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
836M4X/Leandrinha
836M4X
2023-11-18T01:05:37Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-18T01:05:37Z
2023-11-18T01:04:28.000Z
2023-11-18T01:04:28
--- license: apache-2.0 ---
[ -0.12853369116783142, -0.18616779148578644, 0.6529126167297363, 0.49436280131340027, -0.193193256855011, 0.2360745668411255, 0.36071979999542236, 0.05056314915418625, 0.5793651342391968, 0.740013837814331, -0.6508103013038635, -0.23783960938453674, -0.7102248668670654, -0.04782580211758613...
null
null
null
null
null
null
null
null
null
null
null
null
null
spasx/ModelosIA
spasx
2023-11-18T01:29:16Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-18T01:29:16Z
2023-11-18T01:28:35.000Z
2023-11-18T01:28:35
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
todi1/pasmr
todi1
2023-11-18T02:08:35Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-18T02:08:35Z
2023-11-18T01:58:05.000Z
2023-11-18T01:58:05
--- license: openrail ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
ianwatts/water_bottle_db
ianwatts
2023-11-18T02:14:34Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-18T02:14:34Z
2023-11-18T02:14:34.000Z
2023-11-18T02:14:34
--- license: mit ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
Davi2586/United_Abominations_Dave_Mustaine_Dataset
Davi2586
2023-11-18T02:28:10Z
0
0
null
[ "region:us" ]
2023-11-18T02:28:10Z
2023-11-18T02:27:19.000Z
2023-11-18T02:27:19
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
Simonk97/DIEUNHI
Simonk97
2023-11-18T02:28:40Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-18T02:28:40Z
2023-11-18T02:28:02.000Z
2023-11-18T02:28:02
--- license: openrail ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
yribeiro/Cau
yribeiro
2023-11-18T03:04:31Z
0
0
null
[ "region:us" ]
2023-11-18T03:04:31Z
2023-11-18T03:03:07.000Z
2023-11-18T03:03:07
Entry not found
[ -0.3227647542953491, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965083122253, 0.7915717959403992, 0.07618629932403564, 0.7746022343635559, 0.2563222348690033, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
yribeiro/cau2
yribeiro
2023-11-18T03:46:51Z
0
0
null
[ "region:us" ]
2023-11-18T03:46:51Z
2023-11-18T03:40:35.000Z
2023-11-18T03:40:35
Entry not found
[ -0.3227647542953491, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965083122253, 0.7915717959403992, 0.07618629932403564, 0.7746022343635559, 0.2563222348690033, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
autumnjohnson/ceti_audio_test
autumnjohnson
2023-11-18T20:10:11Z
0
0
null
[ "region:us" ]
2023-11-18T20:10:11Z
2023-11-18T06:00:02.000Z
2023-11-18T06:00:02
--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: coda_type dtype: string - name: path dtype: string - name: sampling_rate dtype: int64 splits: - name: train num_bytes: 329883509.875 num_examples: 3529 download_size: 0 dataset_size: 329883509.875 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "ceti_audio_test" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.7849962711334229, -0.4399243891239166, 0.25380077958106995, 0.25470396876335144, 0.003960613161325455, -0.1775469034910202, -0.14550144970417023, -0.20875567197799683, 0.7021110653877258, 0.17857402563095093, -0.7823520302772522, -0.7940106987953186, -0.4658381938934326, -0.365570485591...
null
null
null
null
null
null
null
null
null
null
null
null
null
WeixiangYan/CodeScope
WeixiangYan
2023-11-19T07:34:20Z
0
0
null
[ "task_categories:translation", "task_categories:text-generation", "size_categories:10M<n<100M", "language:en", "language:code", "license:cc-by-nc-4.0", "code", "region:us" ]
2023-11-19T07:34:20Z
2023-11-18T06:11:52.000Z
2023-11-18T06:11:52
--- license: cc-by-nc-4.0 task_categories: - translation - text-generation language: - en - code tags: - code size_categories: - 10M<n<100M ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
vic0428/imdb-card-pred-scientific
vic0428
2023-11-18T06:17:42Z
0
0
null
[ "region:us" ]
2023-11-18T06:17:42Z
2023-11-18T06:13:21.000Z
2023-11-18T06:13:21
--- dataset_info: features: - name: text dtype: string - name: prompt dtype: string - name: true_cardinality dtype: int64 splits: - name: train num_bytes: 39344995.2 num_examples: 80000 - name: test num_bytes: 9836248.8 num_examples: 20000 download_size: 8634654 dataset_size: 49181244.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset Card for "imdb-card-pred-scientific" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.8183668255805969, -0.11502759903669357, 0.21109329164028168, 0.18632587790489197, -0.5642524361610413, 0.2172791212797165, 0.27165737748146057, -0.08583433926105499, 1.1538351774215698, 0.4234975278377533, -0.976453959941864, -0.746347963809967, -0.8144079446792603, -0.02866274863481521...
null
null
null
null
null
null
null
null
null
null
null
null
null
OmarShIT/Omardata1
OmarShIT
2023-11-18T06:36:43Z
0
0
null
[ "region:us" ]
2023-11-18T06:36:43Z
2023-11-18T06:36:43.000Z
2023-11-18T06:36:43
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
ClarenceTKX/wav2vec2-commonvoice-technicaltest
ClarenceTKX
2023-11-18T06:38:38Z
0
0
null
[ "region:us" ]
2023-11-18T06:38:38Z
2023-11-18T06:38:38.000Z
2023-11-18T06:38:38
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
ludis/foundational_rp
ludis
2023-11-20T22:16:07Z
0
0
null
[ "region:us" ]
2023-11-20T22:16:07Z
2023-11-18T06:58:47.000Z
2023-11-18T06:58:47
i am tim dettmers no 1 fan
[ -1.0808932781219482, -0.036662425845861435, 0.31539973616600037, 0.2236441671848297, -0.5332344174385071, 0.05850641801953316, 0.5541192889213562, 0.5083228945732117, 0.7105772495269775, 0.8173868060112, -0.8580922484397888, 0.10798198729753494, -0.8949569463729858, 0.5542957186698914, -...
null
null
null
null
null
null
null
null
null
null
null
null
null
jeje910/oxfordpets_test
jeje910
2023-11-18T07:27:11Z
0
0
null
[ "region:us" ]
2023-11-18T07:27:11Z
2023-11-18T07:27:11.000Z
2023-11-18T07:27:11
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
talaviyabhavik/distillation
talaviyabhavik
2023-11-18T07:38:21Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-18T07:38:21Z
2023-11-18T07:32:49.000Z
2023-11-18T07:32:49
--- license: apache-2.0 --- **Description**: Snapshot measurements on 27 variables from a distillation column; measured over 2.5 years. **Data source**: From an industrial source; variable names have been coded. e.g. Temp1 is a temperature, but we cannot disclose where it is measured on the column. Temperatures are in Fahrenheit Pressures are measured in bars FlowC1 in units of MSCFD FlowC3 and FlowC4 are in units of MBPD Temp11 = Temp3 - Temp9 = the temperature increase of the stream leaving the column and returning back, after passing through the reboiler InvTemp tags are 1000/temperature, therefore with units of inverted Fahrenheit The last column, VapourPressure, is a quality variable measured in the laboratory. The other snapshot measurements in the row correspond to the process conditions when the sample was taken. **Data shape** 253 rows and 27 columns
[ -0.5591194033622742, -0.37663403153419495, 0.583001434803009, 0.3426809012889862, -0.5878073573112488, -0.10786840319633484, 0.3537384867668152, 0.3015642762184143, 0.3226710259914398, 0.4851612150669098, -0.48600929975509644, -0.5740691423416138, -0.5674926042556763, 0.248170405626297, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
joeSmith0101/d1
joeSmith0101
2023-11-18T07:39:25Z
0
0
null
[ "region:us" ]
2023-11-18T07:39:25Z
2023-11-18T07:39:25.000Z
2023-11-18T07:39:25
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
liangzid/nlu_prompts
liangzid
2023-11-18T07:48:22Z
0
0
null
[ "region:us" ]
2023-11-18T07:48:22Z
2023-11-18T07:48:08.000Z
2023-11-18T07:48:08
Entry not found
[ -0.32276472449302673, -0.22568407654762268, 0.8622258901596069, 0.4346148371696472, -0.5282984972000122, 0.7012965679168701, 0.7915717363357544, 0.07618629932403564, 0.7746022939682007, 0.2563222646713257, -0.785281777381897, -0.22573848068714142, -0.9104482531547546, 0.5715669393539429, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
JosephusCheung/naidiffusionv3distil
JosephusCheung
2023-11-18T17:39:56Z
0
8
null
[ "region:us" ]
2023-11-18T17:39:56Z
2023-11-18T08:00:50.000Z
2023-11-18T08:00:50
Single Danbooru-Tag text input, intended for recalibration of Cross-Attention. Word frequency cutoff: tags with at least 1000 posts. ```python safe_file_name = re.sub(r'[^\w\-_\. ]', '_', prompt) file_name = f"{seed_folder}/{safe_file_name}_{seed}.png" ```
[ -0.7137008905410767, -0.9657542109489441, 0.013849613256752491, 0.632196307182312, -0.7864459753036499, -0.1266338974237442, -0.061490315943956375, 0.13132333755493164, 0.31154802441596985, 0.21172048151493073, -0.7050440907478333, -0.6827853322029114, -0.6599650382995605, 0.59201663732528...
null
null
null
null
null
null
null
null
null
null
null
null
null
LimeryJorge/Iris-Image
LimeryJorge
2023-11-18T08:33:41Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-18T08:33:41Z
2023-11-18T08:26:43.000Z
2023-11-18T08:26:43
--- license: apache-2.0 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
q21/embeddings1_autogpt
q21
2023-11-18T08:29:00Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-18T08:29:00Z
2023-11-18T08:29:00.000Z
2023-11-18T08:29:00
--- license: mit ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
zhanjun/mmgpt
zhanjun
2023-11-18T09:33:32Z
0
0
null
[ "region:us" ]
2023-11-18T09:33:32Z
2023-11-18T08:56:19.000Z
2023-11-18T08:56:19
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
apsr/col783_dataset
apsr
2023-11-18T09:20:50Z
0
0
null
[ "region:us" ]
2023-11-18T09:20:50Z
2023-11-18T09:20:44.000Z
2023-11-18T09:20:44
--- dataset_info: features: - name: input_image dtype: image - name: edit_prompt dtype: string - name: edited_image dtype: image splits: - name: train num_bytes: 27683296.0 num_examples: 296 download_size: 27677426 dataset_size: 27683296.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
thanaphatt1/LongAlpaca-16kcontext-th
thanaphatt1
2023-11-18T09:52:02Z
0
0
null
[ "region:us" ]
2023-11-18T09:52:02Z
2023-11-18T09:51:50.000Z
2023-11-18T09:51:50
--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 663099760 num_examples: 9694 download_size: 235774817 dataset_size: 663099760 configs: - config_name: default data_files: - split: train path: data/train-* ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
KhaoulaEL/keypointdetection
KhaoulaEL
2023-11-18T10:00:04Z
0
0
null
[ "region:us" ]
2023-11-18T10:00:04Z
2023-11-18T10:00:04.000Z
2023-11-18T10:00:04
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
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Birchlabs/sdxl-latents-artbench
Birchlabs
2023-11-22T22:39:15Z
0
0
null
[ "region:us" ]
2023-11-22T22:39:15Z
2023-11-18T10:30:38.000Z
2023-11-18T10:30:38
[https://github.com/liaopeiyuan/artbench](ArtBench) samples encoded to float16 SDXL latents via [Ollin VAE](https://huggingface.co/madebyollin/sdxl-vae-fp16-fix). Dataset created using [this script](https://github.com/Birch-san/sdxl-diffusion-decoder/blob/main/script/make_sdxl_latent_dataset.py). Didn't bother saving mean & logvar, because variance is low enough it's not worth the doubling of filesize to retain. Sampled from diagonal gaussian distribution, saved the resulting latents. Also kept the original image. Schema/usage: ```python from typing import TypedDict, Iterator from webdataset import WebDataset Sample = TypedDict('Sample', { '__key__': str, '__url__': str, 'cls.txt': bytes, # UTF-8 encoded class id from 0 to 9 inclusive 'img.png': bytes, # PIL image, serialized. 256*256px 'latent.pth': bytes, # FloatTensor, serialized. 32*32 latents }) it: Iterator[Sample] = WebDataset('train/{00000..00004}.tar') for sample in it: pass ``` The data sources of ArtBench-10 is released under a Fair Use license, as requested by WikiArt, Ukiyo-e.org database and The Surrealism Website. For more information, see https://www.wikiart.org/en/terms-of-use, https://ukiyo-e.org/about and https://surrealism.website/ train: 50000 samples test: 10000 samples ```python # test/avg/val.pt (mean): [-0.11362826824188232, -0.7059057950973511, 0.4819808006286621, 2.2327630519866943] # test/avg/sq.pt: [52.59075927734375, 30.115631103515625, 44.977020263671875, 30.228885650634766] # std # (sq - val**2)**.5 [7.251058578491211, 5.442180633544922, 6.689148902893066, 5.024306297302246] # 1/std [0.1379109025001526, 0.18374986946582794, 0.14949584007263184, 0.19903245568275452] # train/avg/val.pt (mean): [-0.1536690890789032, -0.7142514586448669, 0.4706766605377197, 2.24863600730896] # train/avg/sq.pt: [51.99677276611328, 30.184646606445312, 44.909732818603516, 30.234216690063477] # std # (sq - val**2)**.5 [7.2092413902282715, 5.447429656982422, 6.68492317199707, 5.017753601074219] # 1/std [0.1387108564376831, 0.18357281386852264, 0.14959034323692322, 0.1992923617362976] ```
[ -0.504715085029602, -0.6108615398406982, 0.5249879360198975, 0.054804522544145584, -0.4284980297088623, -0.3143158257007599, 0.03452641889452934, -0.13963142037391663, 0.6354498267173767, 0.15226396918296814, -0.358625203371048, -0.7472597360610962, -0.3659259080886841, -0.2944699823856354...
null
null
null
null
null
null
null
null
null
null
null
null
null
yfchen7/steam
yfchen7
2023-11-18T10:39:38Z
0
0
null
[ "region:us" ]
2023-11-18T10:39:38Z
2023-11-18T10:38:21.000Z
2023-11-18T10:38:21
Entry not found
[ -0.3227645754814148, -0.22568479180335999, 0.8622263669967651, 0.43461522459983826, -0.52829909324646, 0.7012971639633179, 0.7915719747543335, 0.07618614286184311, 0.774603009223938, 0.2563217282295227, -0.7852813005447388, -0.22573819756507874, -0.9104475975036621, 0.5715674161911011, -...
null
null
null
null
null
null
null
null
null
null
null
null
null
jzjiao/truthfulqa-sft
jzjiao
2023-11-18T11:13:28Z
0
0
null
[ "region:us" ]
2023-11-18T11:13:28Z
2023-11-18T11:13:14.000Z
2023-11-18T11:13:14
--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: input dtype: string - name: ground_truth_output dtype: string splits: - name: train num_bytes: 3361565 num_examples: 5918 download_size: 335400 dataset_size: 3361565 --- # Dataset Card for "truthfulqa-sft" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
[ -0.4395594596862793, -0.34643277525901794, 0.3607434332370758, 0.24121400713920593, -0.17541715502738953, 0.18717727065086365, 0.42588359117507935, -0.055140357464551926, 0.5707897543907166, 0.6043460965156555, -0.906069815158844, -0.6829167008399963, -0.35804522037506104, -0.3144163191318...
null
null
null
null
null
null
null
null
null
null
null
null
null
BangumiBase/helck
BangumiBase
2023-11-18T12:49:40Z
0
0
null
[ "size_categories:1K<n<10K", "license:mit", "art", "region:us" ]
2023-11-18T12:49:40Z
2023-11-18T11:19:17.000Z
2023-11-18T11:19:17
--- license: mit tags: - art size_categories: - 1K<n<10K --- # Bangumi Image Base of Helck This is the image base of bangumi Helck, we detected 45 characters, 2595 images in total. The full dataset is [here](all.zip). **Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train models using this dataset, we recommend performing necessary preprocessing on the downloaded dataset to eliminate potential noisy samples (approximately 1% probability). Here is the characters' preview: | # | Images | Download | Preview 1 | Preview 2 | Preview 3 | Preview 4 | Preview 5 | Preview 6 | Preview 7 | Preview 8 | |:------|---------:|:---------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------|:-------------------------------| | 0 | 570 | [Download](0/dataset.zip) | ![preview 1](0/preview_1.png) | ![preview 2](0/preview_2.png) | ![preview 3](0/preview_3.png) | ![preview 4](0/preview_4.png) | ![preview 5](0/preview_5.png) | ![preview 6](0/preview_6.png) | ![preview 7](0/preview_7.png) | ![preview 8](0/preview_8.png) | | 1 | 50 | [Download](1/dataset.zip) | ![preview 1](1/preview_1.png) | ![preview 2](1/preview_2.png) | ![preview 3](1/preview_3.png) | ![preview 4](1/preview_4.png) | ![preview 5](1/preview_5.png) | ![preview 6](1/preview_6.png) | ![preview 7](1/preview_7.png) | ![preview 8](1/preview_8.png) | | 2 | 39 | [Download](2/dataset.zip) | ![preview 1](2/preview_1.png) | ![preview 2](2/preview_2.png) | ![preview 3](2/preview_3.png) | ![preview 4](2/preview_4.png) | ![preview 5](2/preview_5.png) | ![preview 6](2/preview_6.png) | ![preview 7](2/preview_7.png) | ![preview 8](2/preview_8.png) | | 3 | 38 | [Download](3/dataset.zip) | ![preview 1](3/preview_1.png) | ![preview 2](3/preview_2.png) | ![preview 3](3/preview_3.png) | ![preview 4](3/preview_4.png) | ![preview 5](3/preview_5.png) | ![preview 6](3/preview_6.png) | ![preview 7](3/preview_7.png) | ![preview 8](3/preview_8.png) | | 4 | 17 | [Download](4/dataset.zip) | ![preview 1](4/preview_1.png) | ![preview 2](4/preview_2.png) | ![preview 3](4/preview_3.png) | ![preview 4](4/preview_4.png) | ![preview 5](4/preview_5.png) | ![preview 6](4/preview_6.png) | ![preview 7](4/preview_7.png) | ![preview 8](4/preview_8.png) | | 5 | 96 | [Download](5/dataset.zip) | ![preview 1](5/preview_1.png) | ![preview 2](5/preview_2.png) | ![preview 3](5/preview_3.png) | ![preview 4](5/preview_4.png) | ![preview 5](5/preview_5.png) | ![preview 6](5/preview_6.png) | ![preview 7](5/preview_7.png) | ![preview 8](5/preview_8.png) | | 6 | 25 | [Download](6/dataset.zip) | ![preview 1](6/preview_1.png) | ![preview 2](6/preview_2.png) | ![preview 3](6/preview_3.png) | ![preview 4](6/preview_4.png) | ![preview 5](6/preview_5.png) | ![preview 6](6/preview_6.png) | ![preview 7](6/preview_7.png) | ![preview 8](6/preview_8.png) | | 7 | 9 | [Download](7/dataset.zip) | ![preview 1](7/preview_1.png) | ![preview 2](7/preview_2.png) | ![preview 3](7/preview_3.png) | ![preview 4](7/preview_4.png) | ![preview 5](7/preview_5.png) | ![preview 6](7/preview_6.png) | ![preview 7](7/preview_7.png) | ![preview 8](7/preview_8.png) | | 8 | 60 | [Download](8/dataset.zip) | ![preview 1](8/preview_1.png) | ![preview 2](8/preview_2.png) | ![preview 3](8/preview_3.png) | ![preview 4](8/preview_4.png) | ![preview 5](8/preview_5.png) | ![preview 6](8/preview_6.png) | ![preview 7](8/preview_7.png) | ![preview 8](8/preview_8.png) | | 9 | 30 | [Download](9/dataset.zip) | ![preview 1](9/preview_1.png) | ![preview 2](9/preview_2.png) | ![preview 3](9/preview_3.png) | ![preview 4](9/preview_4.png) | ![preview 5](9/preview_5.png) | ![preview 6](9/preview_6.png) | ![preview 7](9/preview_7.png) | ![preview 8](9/preview_8.png) | | 10 | 42 | [Download](10/dataset.zip) | ![preview 1](10/preview_1.png) | ![preview 2](10/preview_2.png) | ![preview 3](10/preview_3.png) | ![preview 4](10/preview_4.png) | ![preview 5](10/preview_5.png) | ![preview 6](10/preview_6.png) | ![preview 7](10/preview_7.png) | ![preview 8](10/preview_8.png) | | 11 | 9 | [Download](11/dataset.zip) | ![preview 1](11/preview_1.png) | ![preview 2](11/preview_2.png) | ![preview 3](11/preview_3.png) | ![preview 4](11/preview_4.png) | ![preview 5](11/preview_5.png) | ![preview 6](11/preview_6.png) | ![preview 7](11/preview_7.png) | ![preview 8](11/preview_8.png) | | 12 | 17 | [Download](12/dataset.zip) | ![preview 1](12/preview_1.png) | ![preview 2](12/preview_2.png) | ![preview 3](12/preview_3.png) | ![preview 4](12/preview_4.png) | ![preview 5](12/preview_5.png) | ![preview 6](12/preview_6.png) | ![preview 7](12/preview_7.png) | ![preview 8](12/preview_8.png) | | 13 | 12 | [Download](13/dataset.zip) | ![preview 1](13/preview_1.png) | ![preview 2](13/preview_2.png) | ![preview 3](13/preview_3.png) | ![preview 4](13/preview_4.png) | ![preview 5](13/preview_5.png) | ![preview 6](13/preview_6.png) | ![preview 7](13/preview_7.png) | ![preview 8](13/preview_8.png) | | 14 | 15 | [Download](14/dataset.zip) | ![preview 1](14/preview_1.png) | ![preview 2](14/preview_2.png) | ![preview 3](14/preview_3.png) | ![preview 4](14/preview_4.png) | ![preview 5](14/preview_5.png) | ![preview 6](14/preview_6.png) | ![preview 7](14/preview_7.png) | ![preview 8](14/preview_8.png) | | 15 | 17 | [Download](15/dataset.zip) | ![preview 1](15/preview_1.png) | ![preview 2](15/preview_2.png) | ![preview 3](15/preview_3.png) | ![preview 4](15/preview_4.png) | ![preview 5](15/preview_5.png) | ![preview 6](15/preview_6.png) | ![preview 7](15/preview_7.png) | ![preview 8](15/preview_8.png) | | 16 | 63 | [Download](16/dataset.zip) | ![preview 1](16/preview_1.png) | ![preview 2](16/preview_2.png) | ![preview 3](16/preview_3.png) | ![preview 4](16/preview_4.png) | ![preview 5](16/preview_5.png) | ![preview 6](16/preview_6.png) | ![preview 7](16/preview_7.png) | ![preview 8](16/preview_8.png) | | 17 | 12 | [Download](17/dataset.zip) | ![preview 1](17/preview_1.png) | ![preview 2](17/preview_2.png) | ![preview 3](17/preview_3.png) | ![preview 4](17/preview_4.png) | ![preview 5](17/preview_5.png) | ![preview 6](17/preview_6.png) | ![preview 7](17/preview_7.png) | ![preview 8](17/preview_8.png) | | 18 | 118 | [Download](18/dataset.zip) | ![preview 1](18/preview_1.png) | ![preview 2](18/preview_2.png) | ![preview 3](18/preview_3.png) | ![preview 4](18/preview_4.png) | ![preview 5](18/preview_5.png) | ![preview 6](18/preview_6.png) | ![preview 7](18/preview_7.png) | ![preview 8](18/preview_8.png) | | 19 | 32 | [Download](19/dataset.zip) | ![preview 1](19/preview_1.png) | ![preview 2](19/preview_2.png) | ![preview 3](19/preview_3.png) | ![preview 4](19/preview_4.png) | ![preview 5](19/preview_5.png) | ![preview 6](19/preview_6.png) | ![preview 7](19/preview_7.png) | ![preview 8](19/preview_8.png) | | 20 | 89 | [Download](20/dataset.zip) | ![preview 1](20/preview_1.png) | ![preview 2](20/preview_2.png) | ![preview 3](20/preview_3.png) | ![preview 4](20/preview_4.png) | ![preview 5](20/preview_5.png) | ![preview 6](20/preview_6.png) | ![preview 7](20/preview_7.png) | ![preview 8](20/preview_8.png) | | 21 | 40 | [Download](21/dataset.zip) | ![preview 1](21/preview_1.png) | ![preview 2](21/preview_2.png) | ![preview 3](21/preview_3.png) | ![preview 4](21/preview_4.png) | ![preview 5](21/preview_5.png) | ![preview 6](21/preview_6.png) | ![preview 7](21/preview_7.png) | ![preview 8](21/preview_8.png) | | 22 | 30 | [Download](22/dataset.zip) | ![preview 1](22/preview_1.png) | ![preview 2](22/preview_2.png) | ![preview 3](22/preview_3.png) | ![preview 4](22/preview_4.png) | ![preview 5](22/preview_5.png) | ![preview 6](22/preview_6.png) | ![preview 7](22/preview_7.png) | ![preview 8](22/preview_8.png) | | 23 | 78 | [Download](23/dataset.zip) | ![preview 1](23/preview_1.png) | ![preview 2](23/preview_2.png) | ![preview 3](23/preview_3.png) | ![preview 4](23/preview_4.png) | ![preview 5](23/preview_5.png) | ![preview 6](23/preview_6.png) | ![preview 7](23/preview_7.png) | ![preview 8](23/preview_8.png) | | 24 | 501 | [Download](24/dataset.zip) | ![preview 1](24/preview_1.png) | ![preview 2](24/preview_2.png) | ![preview 3](24/preview_3.png) | ![preview 4](24/preview_4.png) | ![preview 5](24/preview_5.png) | ![preview 6](24/preview_6.png) | ![preview 7](24/preview_7.png) | ![preview 8](24/preview_8.png) | | 25 | 40 | [Download](25/dataset.zip) | ![preview 1](25/preview_1.png) | ![preview 2](25/preview_2.png) | ![preview 3](25/preview_3.png) | ![preview 4](25/preview_4.png) | ![preview 5](25/preview_5.png) | ![preview 6](25/preview_6.png) | ![preview 7](25/preview_7.png) | ![preview 8](25/preview_8.png) | | 26 | 44 | [Download](26/dataset.zip) | ![preview 1](26/preview_1.png) | ![preview 2](26/preview_2.png) | ![preview 3](26/preview_3.png) | ![preview 4](26/preview_4.png) | ![preview 5](26/preview_5.png) | ![preview 6](26/preview_6.png) | ![preview 7](26/preview_7.png) | ![preview 8](26/preview_8.png) | | 27 | 19 | [Download](27/dataset.zip) | ![preview 1](27/preview_1.png) | ![preview 2](27/preview_2.png) | ![preview 3](27/preview_3.png) | ![preview 4](27/preview_4.png) | ![preview 5](27/preview_5.png) | ![preview 6](27/preview_6.png) | ![preview 7](27/preview_7.png) | ![preview 8](27/preview_8.png) | | 28 | 20 | [Download](28/dataset.zip) | ![preview 1](28/preview_1.png) | ![preview 2](28/preview_2.png) | ![preview 3](28/preview_3.png) | ![preview 4](28/preview_4.png) | ![preview 5](28/preview_5.png) | ![preview 6](28/preview_6.png) | ![preview 7](28/preview_7.png) | ![preview 8](28/preview_8.png) | | 29 | 19 | [Download](29/dataset.zip) | ![preview 1](29/preview_1.png) | ![preview 2](29/preview_2.png) | ![preview 3](29/preview_3.png) | ![preview 4](29/preview_4.png) | ![preview 5](29/preview_5.png) | ![preview 6](29/preview_6.png) | ![preview 7](29/preview_7.png) | ![preview 8](29/preview_8.png) | | 30 | 17 | [Download](30/dataset.zip) | ![preview 1](30/preview_1.png) | ![preview 2](30/preview_2.png) | ![preview 3](30/preview_3.png) | ![preview 4](30/preview_4.png) | ![preview 5](30/preview_5.png) | ![preview 6](30/preview_6.png) | ![preview 7](30/preview_7.png) | ![preview 8](30/preview_8.png) | | 31 | 44 | [Download](31/dataset.zip) | ![preview 1](31/preview_1.png) | ![preview 2](31/preview_2.png) | ![preview 3](31/preview_3.png) | ![preview 4](31/preview_4.png) | ![preview 5](31/preview_5.png) | ![preview 6](31/preview_6.png) | ![preview 7](31/preview_7.png) | ![preview 8](31/preview_8.png) | | 32 | 7 | [Download](32/dataset.zip) | ![preview 1](32/preview_1.png) | ![preview 2](32/preview_2.png) | ![preview 3](32/preview_3.png) | ![preview 4](32/preview_4.png) | ![preview 5](32/preview_5.png) | ![preview 6](32/preview_6.png) | ![preview 7](32/preview_7.png) | N/A | | 33 | 79 | [Download](33/dataset.zip) | ![preview 1](33/preview_1.png) | ![preview 2](33/preview_2.png) | ![preview 3](33/preview_3.png) | ![preview 4](33/preview_4.png) | ![preview 5](33/preview_5.png) | ![preview 6](33/preview_6.png) | ![preview 7](33/preview_7.png) | ![preview 8](33/preview_8.png) | | 34 | 11 | [Download](34/dataset.zip) | ![preview 1](34/preview_1.png) | ![preview 2](34/preview_2.png) | ![preview 3](34/preview_3.png) | ![preview 4](34/preview_4.png) | ![preview 5](34/preview_5.png) | ![preview 6](34/preview_6.png) | ![preview 7](34/preview_7.png) | ![preview 8](34/preview_8.png) | | 35 | 18 | [Download](35/dataset.zip) | ![preview 1](35/preview_1.png) | ![preview 2](35/preview_2.png) | ![preview 3](35/preview_3.png) | ![preview 4](35/preview_4.png) | ![preview 5](35/preview_5.png) | ![preview 6](35/preview_6.png) | ![preview 7](35/preview_7.png) | ![preview 8](35/preview_8.png) | | 36 | 45 | [Download](36/dataset.zip) | ![preview 1](36/preview_1.png) | ![preview 2](36/preview_2.png) | ![preview 3](36/preview_3.png) | ![preview 4](36/preview_4.png) | ![preview 5](36/preview_5.png) | ![preview 6](36/preview_6.png) | ![preview 7](36/preview_7.png) | ![preview 8](36/preview_8.png) | | 37 | 20 | [Download](37/dataset.zip) | ![preview 1](37/preview_1.png) | ![preview 2](37/preview_2.png) | ![preview 3](37/preview_3.png) | ![preview 4](37/preview_4.png) | ![preview 5](37/preview_5.png) | ![preview 6](37/preview_6.png) | ![preview 7](37/preview_7.png) | ![preview 8](37/preview_8.png) | | 38 | 12 | [Download](38/dataset.zip) | ![preview 1](38/preview_1.png) | ![preview 2](38/preview_2.png) | ![preview 3](38/preview_3.png) | ![preview 4](38/preview_4.png) | ![preview 5](38/preview_5.png) | ![preview 6](38/preview_6.png) | ![preview 7](38/preview_7.png) | ![preview 8](38/preview_8.png) | | 39 | 9 | [Download](39/dataset.zip) | ![preview 1](39/preview_1.png) | ![preview 2](39/preview_2.png) | ![preview 3](39/preview_3.png) | ![preview 4](39/preview_4.png) | ![preview 5](39/preview_5.png) | ![preview 6](39/preview_6.png) | ![preview 7](39/preview_7.png) | ![preview 8](39/preview_8.png) | | 40 | 30 | [Download](40/dataset.zip) | ![preview 1](40/preview_1.png) | ![preview 2](40/preview_2.png) | ![preview 3](40/preview_3.png) | ![preview 4](40/preview_4.png) | ![preview 5](40/preview_5.png) | ![preview 6](40/preview_6.png) | ![preview 7](40/preview_7.png) | ![preview 8](40/preview_8.png) | | 41 | 10 | [Download](41/dataset.zip) | ![preview 1](41/preview_1.png) | ![preview 2](41/preview_2.png) | ![preview 3](41/preview_3.png) | ![preview 4](41/preview_4.png) | ![preview 5](41/preview_5.png) | ![preview 6](41/preview_6.png) | ![preview 7](41/preview_7.png) | ![preview 8](41/preview_8.png) | | 42 | 10 | [Download](42/dataset.zip) | ![preview 1](42/preview_1.png) | ![preview 2](42/preview_2.png) | ![preview 3](42/preview_3.png) | ![preview 4](42/preview_4.png) | ![preview 5](42/preview_5.png) | ![preview 6](42/preview_6.png) | ![preview 7](42/preview_7.png) | ![preview 8](42/preview_8.png) | | 43 | 6 | [Download](43/dataset.zip) | ![preview 1](43/preview_1.png) | ![preview 2](43/preview_2.png) | ![preview 3](43/preview_3.png) | ![preview 4](43/preview_4.png) | ![preview 5](43/preview_5.png) | ![preview 6](43/preview_6.png) | N/A | N/A | | noise | 126 | [Download](-1/dataset.zip) | ![preview 1](-1/preview_1.png) | ![preview 2](-1/preview_2.png) | ![preview 3](-1/preview_3.png) | ![preview 4](-1/preview_4.png) | ![preview 5](-1/preview_5.png) | ![preview 6](-1/preview_6.png) | ![preview 7](-1/preview_7.png) | ![preview 8](-1/preview_8.png) |
[ -0.6745119690895081, -0.11414017528295517, 0.10248731821775436, 0.21858733892440796, -0.27343428134918213, -0.03332546353340149, -0.07599470764398575, -0.3734012246131897, 0.5907829403877258, 0.5382682681083679, -0.9315424561500549, -0.9007330536842346, -0.6934003233909607, 0.5312615036964...
null
null
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null
null
null
null
null
null
Pablao0948/Datena
Pablao0948
2023-11-18T11:43:53Z
0
0
null
[ "license:openrail", "region:us" ]
2023-11-18T11:43:53Z
2023-11-18T11:40:50.000Z
2023-11-18T11:40:50
--- license: openrail ---
[ -0.12853363156318665, -0.1861676573753357, 0.6529127359390259, 0.4943627119064331, -0.19319328665733337, 0.23607459664344788, 0.3607197105884552, 0.050563324242830276, 0.5793654322624207, 0.7400139570236206, -0.6508101224899292, -0.2378395050764084, -0.7102251648902893, -0.0478259027004241...
null
null
null
null
null
null
null
null
null
null
null
null
null
pihalf/ERBD
pihalf
2023-11-19T02:27:03Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-19T02:27:03Z
2023-11-18T11:42:24.000Z
2023-11-18T11:42:24
--- license: mit --- This is the dataset from the paper GAST: Geometry-Aware Structure Transformer Will be released before WACV2024
[ -0.3751329779624939, -0.34157368540763855, 0.21040432155132294, 0.029790062457323074, 0.29963794350624084, -0.17438247799873352, 0.23337115347385406, -0.18412338197231293, 0.07945340871810913, 0.7603345513343811, -0.9908828735351562, -0.5965927243232727, -0.22923699021339417, -0.6848039031...
null
null
null
null
null
null
null
null
null
null
null
null
null
sudarajantamilan/whatsthedataset
sudarajantamilan
2023-11-18T11:53:00Z
0
0
null
[ "region:us" ]
2023-11-18T11:53:00Z
2023-11-18T11:50:46.000Z
2023-11-18T11:50:46
Entry not found
[ -0.3227648437023163, -0.22568388283252716, 0.8622258901596069, 0.4346148371696472, -0.5282987356185913, 0.7012966275215149, 0.7915716171264648, 0.07618634402751923, 0.7746025919914246, 0.2563219666481018, -0.7852815389633179, -0.22573809325695038, -0.9104482531547546, 0.5715671181678772, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
yribeiro/caustam
yribeiro
2023-11-18T12:19:22Z
0
0
null
[ "region:us" ]
2023-11-18T12:19:22Z
2023-11-18T12:18:58.000Z
2023-11-18T12:18:58
Entry not found
[ -0.3227648437023163, -0.22568388283252716, 0.8622258901596069, 0.4346148371696472, -0.5282987356185913, 0.7012966275215149, 0.7915716171264648, 0.07618634402751923, 0.7746025919914246, 0.2563219666481018, -0.7852815389633179, -0.22573809325695038, -0.9104482531547546, 0.5715671181678772, ...
null
null
null
null
null
null
null
null
null
null
null
null
null
yribeiro/caustan
yribeiro
2023-11-18T12:24:11Z
0
0
null
[ "region:us" ]
2023-11-18T12:24:11Z
2023-11-18T12:23:57.000Z
2023-11-18T12:23:57
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
kipro/00
kipro
2023-11-18T12:37:12Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-18T12:37:12Z
2023-11-18T12:37:12.000Z
2023-11-18T12:37:12
--- license: apache-2.0 ---
[ -0.12853367626667023, -0.18616794049739838, 0.6529126763343811, 0.4943627417087555, -0.19319313764572144, 0.23607443273067474, 0.36071979999542236, 0.05056338757276535, 0.5793654322624207, 0.7400138974189758, -0.6508103013038635, -0.23783987760543823, -0.710224986076355, -0.047825977206230...
null
null
null
null
null
null
null
null
null
null
null
null
null
kmok1/eng_tswang
kmok1
2023-11-18T12:42:25Z
0
0
null
[ "region:us" ]
2023-11-18T12:42:25Z
2023-11-18T12:40:11.000Z
2023-11-18T12:40:11
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
sczssczxz/ventii
sczssczxz
2023-11-18T13:14:38Z
0
0
null
[ "region:us" ]
2023-11-18T13:14:38Z
2023-11-18T12:41:36.000Z
2023-11-18T12:41:36
Entry not found
[ -0.3227649927139282, -0.225684255361557, 0.862226128578186, 0.43461498618125916, -0.5282987952232361, 0.7012963891029358, 0.7915717363357544, 0.07618629932403564, 0.7746025919914246, 0.2563219666481018, -0.7852816581726074, -0.2257382869720459, -0.9104480743408203, 0.5715669393539429, -0...
null
null
null
null
null
null
null
null
null
null
null
null
null
boinc/test
boinc
2023-11-18T13:01:18Z
0
0
null
[ "license:apache-2.0", "region:us" ]
2023-11-18T13:01:18Z
2023-11-18T13:01:18.000Z
2023-11-18T13:01:18
--- license: apache-2.0 ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
john97843/fr-law-stad
john97843
2023-11-18T13:02:30Z
0
0
null
[ "region:us" ]
2023-11-18T13:02:30Z
2023-11-18T13:01:34.000Z
2023-11-18T13:01:34
french law about STAD
[ -0.19659177958965302, -0.6591180562973022, 0.5751367211341858, 0.8648985624313354, -0.43887847661972046, -0.4454538822174072, 0.02255880832672119, -0.40705251693725586, 0.3951416611671448, 1.2255170345306396, 0.0050954692997038364, -0.3481404483318329, -0.9686088562011719, -0.3509879708290...
null
null
null
null
null
null
null
null
null
null
null
null
null
KnutJaegersberg/prompt_research_datasets
KnutJaegersberg
2023-11-18T13:15:01Z
0
0
null
[ "license:mit", "region:us" ]
2023-11-18T13:15:01Z
2023-11-18T13:15:01.000Z
2023-11-18T13:15:01
--- license: mit ---
[ -0.12853392958641052, -0.18616779148578644, 0.6529127955436707, 0.49436280131340027, -0.19319361448287964, 0.23607419431209564, 0.36072003841400146, 0.050563063472509384, 0.579365611076355, 0.7400140762329102, -0.6508104205131531, -0.23783954977989197, -0.7102249264717102, -0.0478260256350...
null
null
null
null
null
null
null
null
null
null
null
null
null
thevox/en-nb-15k
thevox
2023-11-18T13:18:52Z
0
0
null
[ "task_categories:translation", "size_categories:10K<n<100K", "language:en", "language:nb", "language:no", "license:mpl-2.0", "region:us" ]
2023-11-18T13:18:52Z
2023-11-18T13:18:02.000Z
2023-11-18T13:18:02
--- license: mpl-2.0 task_categories: - translation language: - en - nb - 'no' pretty_name: English-Norwegian Translation size_categories: - 10K<n<100K --- ## Methadology Used GPT-3.5 with a translation prompt to give two versions of translation in Norwegian from English - normal and "more natural". Context is also generated. ## Data Input sample format: ``` Oversett til Norsk: {text} ``` Each output sample is formatted like this: ``` Kontekst: {a, b, c} Oversettelse: {translation} Mer naturlig: {improved_translation} ``` ## Future work Dataset will be used to train LLM-based translation models based on LLama 2 and similar to try to rival DeepL and ChatGPT machine translation. ## Dataset used Original english text from: [nampdn-ai/tiny-textbooks](https://huggingface.co/datasets/nampdn-ai/tiny-textbooks) ### Author Contaxt jonaslsa@uio.no
[ 0.08415631204843521, -0.6070577502250671, 0.6394715309143066, -0.08232032507658005, -0.6745636463165283, -0.352958619594574, -0.23784367740154266, -0.33285006880760193, 0.16723063588142395, 0.8003169894218445, -0.48791101574897766, -0.7339211702346802, -0.48389896750450134, 0.6776102185249...
null
null
null
null
null
null
null
null
null
null
null
null
null