Showing 5 open source projects for "ofn-export-layers"

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  • 1
    TorchServe

    TorchServe

    Serve, optimize and scale PyTorch models in production

    TorchServe is a performant, flexible and easy-to-use tool for serving PyTorch eager mode and torschripted models. Multi-model management with the optimized worker to model allocation. REST and gRPC support for batched inference. Export your model for optimized inference. Torchscript out of the box, ORT, IPEX, TensorRT, FasterTransformer. Performance Guide: built-in support to optimize, benchmark and profile PyTorch and TorchServe performance. Expressive handlers: An expressive handler architecture that makes it trivial to support inferencing for your use case with many supported out of the box. ...
    Downloads: 0 This Week
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  • 2
    Oryx

    Oryx

    Lambda architecture on Apache Spark, Apache Kafka for real-time

    Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein...
    Downloads: 1 This Week
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  • 3
    GUAJE FUZZY

    GUAJE FUZZY

    Free software for generating understandable and accurate fuzzy systems

    GUAJE stands for Generating Understandable and Accurate fuzzy models in a Java Environment. Thus, it is a free software tool (licensed under GPL-v3) with the aim of supporting the design of interpretable and accurate fuzzy systems by means of combining several preexisting open source tools, taking profit from the main advantages of all of them. It is a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy systems, paying...
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  • 4

    Black Hole Cortex

    Sphere surface layers of visual cortex approach maximum info density

    Near the surface (even horizon) of a black hole, there is maximum information density in units of squared plancks (and some translation to qubits). Similarly, our imagination is the set of all possible things we can draw onto our most dense layer of visual cortex in electricity patterns. Bigger layers have more neurons to handle those possibilities. A Black Hole Cortex is a kind of visual cortex that has density of neuron layers similar to density at various radius from a black hole. What we think our eyes see, the imagination, is the densest and smallest layer. SphereSurfaces outside it recursively have more neurons, more surface area, but less density since it has to eventually dimension-reduce to high level ideas, like there are 10000 Wikipedia page names that cover most parts of the world. ...
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    Cerberus FTP Server delivers SOC 2 Type II certified security and FIPS 140-2 validated encryption.

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  • 5
    Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
    Downloads: 0 This Week
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