Showing 5 open source projects for "bootable disk format"

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  • 1
    whisper.cpp

    whisper.cpp

    Port of OpenAI's Whisper model in C/C++

    ...The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples. whisper.cpp supports integer quantization of the Whisper ggml models. Quantized models require less memory and disk space and depending on the hardware can be processed more efficiently.
    Downloads: 434 This Week
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  • 2
    Paperless-ngx

    Paperless-ngx

    A community-supported supercharged version of paperless

    Paperless-ngx is a community-supported open-source document management system that transforms your physical documents into a searchable online archive so you can keep, well, less paper.
    Downloads: 16 This Week
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  • 3
    AnyTXT Searcher

    AnyTXT Searcher

    A Powerful Desktop Full-Text Search Engine, Just Like Local Google.

    ...Mind Map Format (lighten, mmap, mm, xmind etc.) OFD .....
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    Downloads: 6,951 This Week
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  • 4
    Paperless-ng

    Paperless-ng

    A supercharged version of paperless, scan, index and archive docs

    Paperless is a simple Django application running in two parts, a Consumer (the thing that does the indexing) and a Web server (the part that lets you search & download already-indexed documents). Paper is a nightmare. Environmental issues aside, there’s no excuse for it in the 21st century. It takes up space, collects dust, doesn’t support any form of a search feature, indexing is tedious, it’s heavy and prone to damage & loss. I wrote this to make “going paperless” easier. I do not have to...
    Downloads: 0 This Week
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  • 5

    GA-EoC

    GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations

    In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets. To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training. To...
    Downloads: 0 This Week
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