Showing 8 open source projects for "router data usage"

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  • 1
    Milvus Bootcamp

    Milvus Bootcamp

    Dealing with all unstructured data, such as reverse image search

    Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications.
    Downloads: 0 This Week
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  • 2
    Amoeba

    Amoeba

    Linux Command Line Learning Program

    Amoeba is a Linux command-line learning program that observes and adapts to the Linux command line storing learned strings and their usage data. It enhances command-line proficiency by capturing command outputs, adapting string lengths, and periodically saving knowledge. Sandboxing is essential for security, and optionally a virtual machine would further isolates it from the host system. Contributions and improvements are encouraged via the GitHub repository.
    Downloads: 1 This Week
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  • 3
    Voconly

    Voconly

    Free, open-source, offline speech-to-text tool for Windows and MacOS.

    **voconly is a free, open-source, local-first AI voice input assistant that runs entirely on your device.** It turns speech into text locally and uses AI to polish, translate, organize, and transform your words into usable content, letting you replace keyboard input with your voice in any application. No audio uploads. No cloud dependency. Your voice stays on your device. Unlike cloud-based voice input software, voconly keeps all audio data local—no uploads, no internet required,...
    Downloads: 5 This Week
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  • 4
    Synonyms

    Synonyms

    Chinese synonyms, chat robot, intelligent question and answer toolkit

    Chinese Synonyms for natural language processing and understanding. Better Chinese synonyms, chatbot, intelligent question and answer toolkit. synonymsCan be used for many tasks in natural language understanding, text alignment, recommendation algorithms, similarity calculation, semantic shifting, keyword extraction, concept extraction, automatic summarization, search engines, etc. Print synonyms in a friendly way for easy debugging. "Synonyms Cilin" was compiled by Mei Jiaju and others in...
    Downloads: 6 This Week
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  • 5
    cocoNLP

    cocoNLP

    A Chinese information extraction tool

    cocoNLP is a lightweight natural-language processing toolkit geared toward practical information extraction from raw text, especially for Chinese and mixed Chinese–English content. Instead of requiring a heavy pipeline, it focuses on quick wins such as extracting names, places, organizations, emails, phone numbers, and dates directly from unstructured sentences. The project blends pattern-based methods with NLP heuristics, giving developers dependable results for real-world texts like chats,...
    Downloads: 0 This Week
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  • 6
    Rasa-UI

    Rasa-UI

    Rasa UI is a frontend for the Rasa Framework

    Rasa UI is a web application built on top of, and for Rasa. Rasa UI provides a web application to quickly and easily be able to create and manage bots, NLU components (Regex, Examples, Entities, Intents, etc.) and Core components (Stories, Actions, Responses, etc.) through a web interface. It also provides some convenience features for Rasa, like training and loading your models, monitoring usage or viewing logs.
    Downloads: 0 This Week
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  • 7
    Gensim-data

    Gensim-data

    Data repository for pretrained NLP models and NLP corpora

    ...Users normally access the catalog through Python or the Gensim command-line downloader rather than cloning the repository itself. Downloads are cached in a local gensim-data directory for later reuse. The collection includes corpora such as text8 and 20 Newsgroups alongside pretrained word-vector resources such as GloVe. Every dataset retains its own licensing terms, so users must review individual usage conditions.
    Downloads: 0 This Week
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  • 8
    CRFSharp

    CRFSharp

    CRFSharp is a .NET(C#) implementation of Conditional Random Field

    ...CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. Currently, when training corpus, compared with CRF++, CRF# can make full use of multi-core CPUs and only uses very low memory, and memory grow is very smoothly and slowly while amount of training corpus, tags increase. with multi-threads process, CRF# is more suitable for large data and tags training than CRF++ now. ...
    Downloads: 0 This Week
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