Showing 9 open source projects for "development tools"

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    Oumi

    Oumi

    Everything you need to build state-of-the-art foundation models

    Oumi is an open-source framework that provides everything needed to build state-of-the-art foundation models, end-to-end. It aims to simplify the development of large-scale machine-learning models.
    Downloads: 6 This Week
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  • 2
    LMDeploy

    LMDeploy

    LMDeploy is a toolkit for compressing, deploying, and serving LLMs

    LMDeploy is a toolkit designed for compressing, deploying, and serving large language models (LLMs). It offers tools and workflows to optimize LLMs for production environments, ensuring efficient performance and scalability. LMDeploy supports various model architectures and provides deployment solutions across different platforms.
    Downloads: 0 This Week
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  • 3
    Intel Extension for Transformers

    Intel Extension for Transformers

    Build your chatbot within minutes on your favorite device

    Intel Extension for Transformers is an innovative toolkit designed to accelerate Transformer-based models on Intel platforms, including CPUs and GPUs. It offers state-of-the-art compression techniques for Large Language Models (LLMs) and provides tools to build chatbots within minutes on various devices. The extension aims to optimize the performance of Transformer-based models, making them more efficient and accessible.
    Downloads: 0 This Week
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  • 4
    Seldon Core

    Seldon Core

    An MLOps framework to package, deploy, monitor and manage models

    The de facto standard open-source platform for rapidly deploying machine learning models on Kubernetes. Seldon Core, our open-source framework, makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and...
    Downloads: 0 This Week
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    AI-generated apps that pass security review

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  • 5
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. ...
    Downloads: 0 This Week
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  • 6
    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox (ART) - Python Library for ML security

    Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio,...
    Downloads: 0 This Week
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  • 7
    towhee

    towhee

    Framework that is dedicated to making neural data processing

    ...We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data.
    Downloads: 0 This Week
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  • 8
    LLMFlows

    LLMFlows

    LLMFlows - Simple, Explicit and Transparent LLM Apps

    LLMFlows is a framework for building simple, explicit, and transparent applications utilizing Large Language Models (LLMs). It emphasizes clarity and control in the development process, allowing developers to create LLM-powered applications with well-defined workflows and interactions. LLMFlows supports various LLMs and provides tools to manage prompts, responses, and application logic effectively.
    Downloads: 0 This Week
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  • 9
    SageMaker MXNet Inference Toolkit

    SageMaker MXNet Inference Toolkit

    Toolkit for allowing inference and serving with MXNet in SageMaker

    SageMaker MXNet Inference Toolkit is an open-source library for serving MXNet models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep...
    Downloads: 0 This Week
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