dc.contributor.author | Terčon, Luka |
dc.contributor.author | Ljubešić, Nikola |
dc.date.accessioned | 2023-04-14T08:35:06Z |
dc.date.available | 2023-04-14T08:35:06Z |
dc.date.issued | 2023-04-11 |
dc.identifier.uri | http://hdl.handle.net/11356/1790 |
dc.description | CLARIN.SI-embed.hr contains word embeddings induced from a large collection of Croatian texts composed of the Croatian web corpus hrWaC, a 400-million-token-heavy collection of newspaper texts and MaCoCu-hr. The embeddings are based on the skip-gram model of fastText trained on 4,586,769,197 tokens of running text for 3,406,574 lowercased surface forms. The difference to the previous version of the embeddings is that this version was trained on the original dataset expanded with the MaCoCu-hr web crawl corpus (http://hdl.handle.net/11356/1516). |
dc.language.iso | hrv |
dc.publisher | Jožef Stefan Institute |
dc.relation.replaces | http://hdl.handle.net/11356/1205 |
dc.rights | Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) |
dc.rights.uri | https://creativecommons.org/licenses/by-sa/4.0/ |
dc.rights.label | PUB |
dc.subject | word embeddings |
dc.title | Word embeddings CLARIN.SI-embed.hr 2.0 |
dc.type | lexicalConceptualResource |
metashare.ResourceInfo#ContentInfo.detailedType | computationalLexicon |
metashare.ResourceInfo#ContentInfo.mediaType | text |
has.files | yes |
branding | CLARIN.SI data & tools |
contact.person | Nikola Ljubešić nikola.ljubesic@ijs.si Jožef Stefan Institute |
contact.person | Luka Terčon luka.tercon@gmail.com Faculty of Computer and Information Science, University of Ljubljana |
sponsor | Jožef Stefan Institute CLARIN CLARIN.SI nationalFunds |
sponsor | ARRS (Slovenian Research Agency) J7-4642 MEZZANINE nationalFunds |
sponsor | Connecting Europe Facility (CEF) Telecom INEA/CEF/ICT/A2020/2278341 MaCoCu - Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages Other |
sponsor | ARRS (Slovenian Research Agency) P6-0411 Language Resources and Technologies for Slovene nationalFunds |
size.info | 3406574 entries |
files.count | 2 |
files.size | 4463896195 |
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- Name
- all-token-hr-prelim.ft.sg.vec.zip
- Size
- 1.08 GB
- Format
- application/zip
- Description
- Token embeddings, text format
- MD5
- d0660acf59d53d4425fb15f07e25b996

- Name
- all-token-hr-prelim.ft.sg.bin.zip
- Size
- 3.08 GB
- Format
- application/zip
- Description
- Token embeddings, binary
- MD5
- 6982e404dc59c2a4bd2bcd2173b5464b