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2 مستودعات

Awesome GitHub RepositoriesCustom ML Components

Extensibility mechanisms for defining custom neural network layers, models, and metrics using high-level language source code.

Distinct from Custom Python Components: Distinct from Custom Python Components: specifically targets ML-specific building blocks like layers and metrics rather than general system logic.

Explore 2 awesome GitHub repositories matching user interface & experience · Custom ML Components. Refine with filters or upvote what's useful.

Awesome Custom ML Components GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • fchollet/kerasالصورة الرمزية لـ fchollet

    fchollet/keras

    64,095عرض على GitHub↗

    Keras is a high-level deep learning API used to design, build, and train neural networks for tasks such as computer vision, natural language processing, and time series forecasting. It provides a framework for defining model architectures and optimizing weights through a structured interface. The project is defined by a backend-agnostic design that allows the same model code to run across different compute engines. This multi-backend execution enables users to swap underlying engines to optimize for specific hardware or performance requirements. The system supports distributed model training

    Enables the creation of custom layers, models, and metrics that remain compatible across different compute engines.

    Python
    عرض على GitHub↗64,095
  • modelscope/modelscopeالصورة الرمزية لـ modelscope

    modelscope/modelscope

    8,718عرض على GitHub↗

    ModelScope is a comprehensive machine learning platform that functions as a model hub, training framework, inference engine, and cloud development environment. It provides a centralized repository for discovering, downloading, and managing pre-trained models and datasets across multiple modalities, including natural language, vision, and speech. The platform features a unified interface for multimodal model inference and a standardized framework for fine-tuning and evaluating large-scale models. It supports distributed training to scale workloads across multiple processors and provides contai

    Allows the modification of specific pipeline modules to implement custom logic during model inference and training.

    Pythoncvdeep-learningmachine-learning
    عرض على GitHub↗8,718
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