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| Hauptseite > Publikationsdatenbank > OpenGPT-X – Training Large Language Models on HPC Systems > print |
| Hauptseite > Publikationsdatenbank > OpenGPT-X – Training Large Language Models on HPC Systems > print |
| 001 | 1007707 | ||
| 005 | 20250822121435.0 | ||
| 024 | 7 | _ | |2 doi |a 10.34732/XDVBLG-SVNDMJ |
| 024 | 7 | _ | |2 Handle |a 2128/34532 |
| 037 | _ | _ | |a FZJ-2023-02173 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |0 P:(DE-Juel1)187395 |a John, Chelsea Maria |b 0 |e Corresponding author |
| 111 | 2 | _ | |a ISC High Performance 2023 |c Hamburg |d 2023-05-21 - 2023-05-25 |g ISC23 |w Germany |
| 245 | _ | _ | |a OpenGPT-X – Training Large Language Models on HPC Systems |
| 260 | _ | _ | |c 2023 |
| 336 | 7 | _ | |0 33 |2 EndNote |a Conference Paper |
| 336 | 7 | _ | |2 BibTeX |a INPROCEEDINGS |
| 336 | 7 | _ | |2 DRIVER |a conferenceObject |
| 336 | 7 | _ | |2 ORCID |a CONFERENCE_POSTER |
| 336 | 7 | _ | |2 DataCite |a Output Types/Conference Poster |
| 336 | 7 | _ | |0 PUB:(DE-HGF)24 |2 PUB:(DE-HGF) |a Poster |b poster |m poster |s 1687163345_9014 |x After Call |
| 520 | _ | _ | |a OpenGPT-X is a German initiative to build and train large language models (LLMs). The project aims at providing an open alternative to LLMs which are up to now private property, along with a platform for researching methods to train multilingual LLMs efficiently. For that, the project not only utilizes the state-of-the-art in training models but also incorporates new methods, algorithms, and tools. Models trained within the project will be published and used for pilot language services by industry partners. In addition, further applications are expected through Gaia-X federation. LLMs can scale to more than 175 Billion parameters, which requires efficient usage of supercomputers like JUWELS Booster. Especially in the light of the recent successes of ChatGPT, our work clearly indicates that the infrastructure of supercomputing centres and initiatives aiming to provide resources to the public can have a large societal impact. This poster outlines the initial progress and future work of the project from Jülich Supercomputing Center (JSC). |
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| 588 | _ | _ | |a Dataset connected to DataCite |
| 650 | _ | 7 | |2 Other |a HPC |
| 650 | _ | 7 | |2 Other |a GPU |
| 650 | _ | 7 | |2 Other |a OpenGPTX |
| 700 | 1 | _ | |0 P:(DE-Juel1)187002 |a Ebert, Jan |b 1 |u fzj |
| 700 | 1 | _ | |0 P:(DE-Juel1)192254 |a Penke, Carolin |b 2 |u fzj |
| 700 | 1 | _ | |0 P:(DE-Juel1)185654 |a Kesselheim, Stefan |b 3 |u fzj |
| 700 | 1 | _ | |0 P:(DE-Juel1)145478 |a Herten, Andreas |b 4 |u fzj |
| 773 | _ | _ | |a 10.34732/XDVBLG-SVNDMJ |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/1007707/files/ISC%202023%20OpenGPT-X%20Project%20Poster.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:1007707 |p openaire |p open_access |p VDB |p driver |
| 910 | 1 | _ | |0 I:(DE-588b)5008462-8 |6 P:(DE-Juel1)187395 |a Forschungszentrum Jülich |b 0 |k FZJ |
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| 913 | 1 | _ | |0 G:(DE-HGF)POF4-512 |1 G:(DE-HGF)POF4-510 |2 G:(DE-HGF)POF4-500 |3 G:(DE-HGF)POF4 |4 G:(DE-HGF)POF |9 G:(DE-HGF)POF4-5121 |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |v Supercomputing & Big Data Infrastructures |x 1 |
| 914 | 1 | _ | |y 2023 |
| 915 | _ | _ | |0 StatID:(DE-HGF)0510 |2 StatID |a OpenAccess |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a poster |
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| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a OPENSCIENCE |
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