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Grafana: The open and composable observability platform
Faster answers, predictable costs, and no lock-in built by the team helping to make observability accessible to anyone.
Grafana is the open source analytics & monitoring solution for every database.
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually refresh supervision signals. ...
PADIC (Parallel Arabic DIalectal Corpus) is a multi-dialectal corpus built in the framework of the National Research Project "TORJMAN", led by Scientific and Technical Research Center for the Development of Arabic Language and funded by the Algerian Ministry of Higher Education and Scientific Research.
PADIC is composed of 6 dialects: two Algerian dialects (Algiers and Annaba cities), Palestinian, Syrian, Tunisian, Moroccan) and MSA.
automatic alignment pipeline for parallel treebanks
The *Tree-to-Tree (t2t) Alignment Pipe* is a collection of python scripts, co-ordinating the process of automatic alignment of parallel treebanks from plain text files with a single call from a unix command line. Supported Languages: DE, FR, EN
Various tools for creating annotated parallel corpora including pre-trained tagging and parsing models for various languages, sentence alignment tools and word alignment tools.
Uplug also includes a web-based interface for interactive sentence and word alignment and scripts for indexing and querying parallel corpora using the Corpus Work Bench CWB.
Download 'uplug-main' first and then add other packages.
OrangeHRM provides a world-class HRIS experience and offers everything you and your team need to be that HR hero you know that you are.
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