text_1 stringlengths 1 23.9k | lang_1 stringclasses 40
values | embedding_1 list | text_2 stringlengths 1 19.7k | lang_2 stringclasses 65
values | embedding_2 list |
|---|---|---|---|---|---|
" ' I will have respect for you , and make you fruitful , and multiply you , and will establish my covenant with you . | eng_Latn | [
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-0.010928777977... | “ मग मी तुमच्याकडे वळेन व तुम्हाला भरपूर संतती देईन आणि तुमच्याशी केलेला माझा करार पक्का करीन ; | mar_Deva | [
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This isn 't information. | eng_Latn | [
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0.00492105772... | यह जानकारी नहीं है. | hin_Deva | [
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On the whole, 'Chilika' is a remarkable achievement. | eng_Latn | [
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-0.008056432008... | कुल मिलाकर देखा जाय तो चिलिका एक असाधरण उपलब्धि है। | hin_Deva | [
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Interestingly , even some opposers recognize the dedication that Jehovah’s Witnesses have made to God to serve him unreservedly . | eng_Latn | [
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... | আগ্রহের বিষয় হল , যিহোবার সাক্ষিরা ঈশ্বরকে পুরোপুরিভাবে সেবা করার জন্য তাঁর কাছে যে - উৎসর্গীকরণ করেছে , এমনকি কিছু বিরোধীও সেটার তাৎপর্য বুঝতে পারে । | ben_Beng | [
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Lot subsequently chose for himself the verdant area of Sodom and Gomorrah . | eng_Latn | [0.01238002348691225,0.001520367804914713,-0.002069193636998534,0.0057025025598704815,-0.00041002521(...TRUNCATED) | "লোট সদোম ও ঘোমরা নামে এক উর্বর জায়গা ব(...TRUNCATED) | ben_Beng | [0.008729067631065845,-0.005981098394840956,-0.005893907509744167,0.010069102048873901,-0.0040309140(...TRUNCATED) |
Franck! | eng_Latn | [0.006675261538475752,0.00641285628080368,0.0018553314730525017,-0.002080086851492524,0.000232798425(...TRUNCATED) | फ़्रैंक! | hin_Deva | [0.012786637991666794,0.002878138329833746,-0.0060315802693367004,0.003768622875213623,0.00360140996(...TRUNCATED) |
"However, within the Scheduled Tribes, women often suffer from a greater disadvantage. Ministry of T(...TRUNCATED) | eng_Latn | [-0.002014151308685541,0.00870396476238966,-0.002024362562224269,-0.02300800010561943,0.008685377426(...TRUNCATED) | "ସେଗୁଡିକ ମଧ୍ୟରୁ ଆଶ୍ରମ ବିଦ୍ୟାଳୟ ଯୋଜନା, (...TRUNCATED) | ory_Orya | [-0.0011299820616841316,0.0014732099371030927,-0.009162893518805504,0.005402769893407822,0.018089547(...TRUNCATED) |
"Meanwhile , Jehovah is directly involved in the lives of his faithful worshippers today . Let us no(...TRUNCATED) | eng_Latn | [-0.006439917255192995,0.0020713089033961296,-0.00442907540127635,-0.005740536376833916,0.0049409219(...TRUNCATED) | "அதே சமயத்தில் , இன்று தம் உண்மை வணக்க(...TRUNCATED) | tam_Taml | [-0.005042898468673229,0.008757011964917183,-0.0052112708799541,0.0013754593674093485,0.006734997499(...TRUNCATED) |
"One young husband relates : “ Before getting married , my wife would always put priority on her p(...TRUNCATED) | eng_Latn | [0.0003085549105890095,-0.008202319033443928,0.0072127459570765495,0.00782020203769207,-0.0040619699(...TRUNCATED) | "એક યુવાન પતિ જણાવે છે : “ લગ્ન પહેલાં મ(...TRUNCATED) | guj_Gujr | [-0.0069680530577898026,0.0022786264307796955,0.006014940328896046,0.009387214668095112,0.0023832893(...TRUNCATED) |
Have We not made the earth as a bed , | eng_Latn | [-0.004804529715329409,0.00976666621863842,0.002760683186352253,-0.011358708143234253,-0.00477852812(...TRUNCATED) | "আমরা কি পৃথিবীটাকে পাতানো-বিছানারূ(...TRUNCATED) | ben_Beng | [-0.00474920216947794,0.010763113386929035,0.00196087290532887,-0.008093041367828846,-0.004090773407(...TRUNCATED) |
End of preview. Expand in Data Studio
What happened to the original dataset? We preprocess the public data and NLLB-Seed, with a note:
aaudataset, except theormlanguage because it is not supported by the SONAR modelhornmtdataset, except theormandaarlanguages because these are not supported by the SONAR modelmburisanodataset, exceptndeandvenlanguages because these are not supported by the SONAR modelticodataset, except theormlanguage because it is not supported by the SONAR modeltildataset because the total size is about ~80.6M pairs, which translates to about ~615 GB
What are the use cases?
- Training a model with embeddings as input. For example, training a Sparse Autoencoder. This saves computation because we do not need to load the encoder during training. Also, we do not need to cache the encoder's output on-the-fly
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