laser_score float64 1.04 1.25 | text1 stringlengths 1 482 | lang1 stringclasses 155
values | embedding1 list | text2 stringlengths 1 499 | lang2 stringclasses 175
values | embedding2 list | blaser_sim float64 3.5 5.72 |
|---|---|---|---|---|---|---|---|
1.229453 | Така че кой съм аз – аз, роденият в САЩ – че да съветвам Русия да се извини? | bul_Cyrl | [
0.0077550169080495834,
0.0012912093661725521,
0.002405794570222497,
-0.007080156356096268,
-0.00556337833404541,
0.0032254739198833704,
-0.008428788743913174,
0.003508265595883131,
0.006031279917806387,
0.004247881006449461,
-0.014419504441320896,
-0.004029272124171257,
0.010674369521439075,... | Так кто же я такой, - я, родившийся в США, - чтобы советовать России принести извинения? | rus_Cyrl | [
0.008474393747746944,
-0.0031286696903407574,
0.002227923832833767,
-0.007525110617280006,
-0.00391716742888093,
0.0022336223628371954,
-0.004861956927925348,
0.008223338052630424,
0.0070099555887281895,
0.007698637433350086,
-0.015512355603277683,
0.001578076626174152,
0.009621787816286087,... | 4.484756 |
1.17397 | Iti daydi a tiempo, adu a Nakristianuan a publikasiontayo ti saan pay a magun-odan iti lengguahemi nga Afrikaans. | ilo_Latn | [
0.0009740008390508592,
-0.0011854018084704876,
0.008275056257843971,
-0.0001694104284979403,
-0.0022197007201611996,
-0.015022939071059227,
-0.0021725317928940058,
-0.014634668827056885,
0.0019836758729070425,
0.001477565965615213,
0.004197764676064253,
-0.0010312574449926615,
0.007570639252... | Hito nga panahon damu han aton mga publikasyon an waray pa ha akon yinaknan nga Afrikaans. | war_Latn | [
-0.0033984780311584473,
-0.0022063548676669598,
0.0035756423603743315,
0.0026913336478173733,
-0.0019124585669487715,
-0.013200688175857067,
0.0028398658614605665,
-0.013464272022247314,
0.005986164789646864,
-0.003436060156673193,
0.008838066831231117,
-0.00676713278517127,
0.00963519886136... | 4.781749 |
1.138165 | 2 Yesu ye tile binaani ni su binaani kè sun na, a ma dumuni kè, o kò, kòngò y'a minè. | bam_Latn | [
-0.008399494923651218,
-0.0026347122620791197,
-0.001494135125540197,
-0.0028213884215801954,
-0.000373234914150089,
0.0006380208069458604,
0.0029151386115700006,
-0.003394431434571743,
0.00824331771582365,
-0.0070181312039494514,
0.002915414283052087,
-0.012524384073913097,
-0.0039472118951... | 24:2 1Ath 19:8Na aniina mĩthenya mĩrongo ĩna, ũtukũ na mũthenya, ehingĩte kũrĩa irio-rĩ, akĩigua ahũtiĩ. | kik_Latn | [
-0.010994229465723038,
-0.007967057637870312,
-0.006844878662377596,
-0.0020831881556659937,
-0.0006035635014995933,
0.00001370824065816123,
-0.00778152234852314,
-0.006277055479586124,
0.009293635375797749,
-0.00557534396648407,
-0.0007063212688080966,
-0.015107330866158009,
-0.001678883796... | 4.421457 |
1.194247 | Meisie, as jy 15, of selfs 12 is, sê ek vir jou dat jou lewe joune is, soos ek pas gesê het. | afr_Latn | [
-0.0086482223123312,
-0.0019005174981430173,
0.009599622339010239,
0.004160834942013025,
0.009718519635498524,
0.0064164805226027966,
-0.0025214499328285456,
0.01250280812382698,
-0.0005781556246802211,
0.005501494277268648,
-0.004275426268577576,
0.009188918396830559,
-0.0026469698641449213... | Girl, if you are 15, or even 12, I tell you that your life is yours, as I just said. | eng_Latn | [
-0.005473778583109379,
-0.0010698697296902537,
0.012267844751477242,
0.00325755774974823,
0.0101967453956604,
0.008712904527783394,
-0.005378759931772947,
0.00907663069665432,
0.00013316648255567998,
0.0023635264951735735,
-0.004872812889516354,
0.005114783067256212,
-0.002982066012918949,
... | 4.416798 |
1.163591 | 7 Komosta karon? | ceb_Latn | [-0.003663931740447879,0.006651561241596937,0.0009477217681705952,-0.00026334929862059653,0.00155972(...TRUNCATED) | 7 Kumusta man yana? | war_Latn | [-0.0014681785833090544,0.005875999573618174,0.00305435829795897,0.0024381265975534916,0.00024180533(...TRUNCATED) | 4.609043 |
1.191229 | - Après 48h de travail avec mes partenaires européens, nous avons un accord ! | fra_Latn | [-0.012442152015864849,0.001338087022304535,0.016184208914637566,0.00009788358875084668,0.0069133052(...TRUNCATED) | "«Після 48 годин роботи з моїми європейськими партнерам(...TRUNCATED) | ukr_Cyrl | [-0.01161973550915718,-0.0025535188615322113,0.01552787609398365,0.0007470527780242264,0.00454251654(...TRUNCATED) | 4.310436 |
1.205764 | Kona frá Moldavíu (ár) til að kynnast manni — ár fyrir fjölskyldu. | isl_Latn | [0.0026735698338598013,-0.003137638559564948,0.007792401593178511,0.005794089753180742,0.00113621272(...TRUNCATED) | Vrouw uit Moldavië (jaar) om kennis te maken met een man — jaren voor een familie. | nld_Latn | [0.0012271859450265765,-0.007992977276444435,0.011831064708530903,0.010752206668257713,0.00210936181(...TRUNCATED) | 4.223686 |
1.11998 | There are two methods to proceed. | eng_Latn | [0.005759960971772671,0.004688852466642857,-0.0027945965994149446,0.00838517490774393,0.010976593941(...TRUNCATED) | Illanat sanatat tikarsiwen i anuttif net | taq_Latn | [-0.006413851398974657,0.006012872792780399,-0.0012793218484148383,0.0009293552720919251,0.003050890(...TRUNCATED) | 3.834981 |
1.244219 | 本当にアッラー（神）は凡てのことに全能であられる。 | jpn_Jpan | [-0.0029160273261368275,-0.008722386322915554,0.00027580015012063086,0.001177699537947774,-0.0031169(...TRUNCATED) | Hakika Mwenyezi Mungu ni Mweza wa kila kitu. | swh_Latn | [-0.004602719098329544,-0.011512386612594128,0.000511623453348875,-0.00041523866821080446,0.00103661(...TRUNCATED) | 4.743254 |
1.231602 | Owetewa, onge tiende ndikonu kuom ndalo kata sa ma gigo notimree, | luo_Latn | [-0.006570375990122557,0.0015227094991132617,0.009390860795974731,0.0016817603027448058,-0.006910012(...TRUNCATED) | Empa haeba linako le mehla, barab'eso, ho na le ke ho hlokahale hore a ngole a re ho uena. | sot_Latn | [-0.005143884103745222,0.006364667788147926,0.008932228200137615,-0.002740254858508706,-0.0122205791(...TRUNCATED) | 4.894472 |
End of preview. Expand in Data Studio
What happens to the original dataset?
- Filter by
blaser_sim >= 3.5 - Add new columns
embedding1andembedding2. The embeddings are generated by SONAR'sTextToEmbeddingModelPipeline
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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