Showing 4 open source projects for "training"

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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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  • 1
    ort

    ort

    Fast ML inference & training for ONNX models in Rust

    ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn. The library emphasizes speed and efficiency, leveraging hardware acceleration across CPUs, GPUs, and specialized accelerators to deliver low-latency inference both on-device and in server environments. ...
    Downloads: 6 This Week
    Last Update:
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  • 2
    Tokenizers

    Tokenizers

    Fast State-of-the-Art Tokenizers optimized for Research and Production

    ...Tokenizers provides an implementation of today’s most used tokenizers, with a focus on performance and versatility. These tokenizers are also used in Transformers. Train new vocabularies and tokenize, using today’s most used tokenizers. Extremely fast (both training and tokenization), thanks to the Rust implementation. Takes less than 20 seconds to tokenize a GB of text on a server’s CPU. Easy to use, but also extremely versatile. Designed for both research and production. Full alignment tracking. Even with destructive normalization, it’s always possible to get the part of the original sentence that corresponds to any token. ...
    Downloads: 5 This Week
    Last Update:
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  • 3
    Burn

    Burn

    Burn is a new comprehensive dynamic Deep Learning Framework

    Burn is a new comprehensive dynamic Deep Learning Framework from Tracel AI built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. Burn emphasizes performance, flexibility, and portability for both training and inference. Developed in Rust, it is designed to empower machine learning engineers and researchers across industry and academia.
    Downloads: 8 This Week
    Last Update:
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  • 4
    ModelFox

    ModelFox

    ModelFox makes it easy to train, deploy, and monitor ML models

    ModelFox makes it easy to train, deploy, and monitor machine learning models. Train a model from a CSV file on the command line. Make predictions from Elixir, Go, JavaScript, PHP, Python, Ruby, or Rust. Learn about your models and monitor them in production from your browser. ModelFox makes it easy to train, deploy, and monitor machine learning models. You can install the modelfox CLI by either downloading the binary from the latest GitHub release or by building from source. Train a machine...
    Downloads: 45 This Week
    Last Update:
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  • Add Two Lines of Code. Get Full APM. Icon
    Add Two Lines of Code. Get Full APM.

    AppSignal installs in minutes and auto-configures dashboards, alerts, and error tracking.

    Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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