5 projects for "logging" with 2 filters applied:

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  • 1
    TNT

    TNT

    A lightweight library for PyTorch training tools and utilities

    ...It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps separate concerns such as model training, evaluation, logging, and checkpointing, making machine learning experiments easier to manage. The framework is particularly useful for large-scale experiments where maintaining clear training workflows becomes increasingly important. Because it is built on top of PyTorch, the framework integrates naturally with existing deep learning models and datasets.
    Downloads: 0 This Week
    Last Update:
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  • 2
    mosaicml composer

    mosaicml composer

    Supercharge Your Model Training

    composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. It includes built-in support for distributed training strategies such as Fully Sharded Data Parallelism and standard Distributed Data Parallel execution, helping teams scale models without having to assemble as much infrastructure by hand.
    Downloads: 6 This Week
    Last Update:
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  • 3
    AI-Job-Notes

    AI-Job-Notes

    AI algorithm position job search strategy

    ...The emphasis is on doing: practicing with project ideas, setting up reproducible experiments, and showcasing results that convey impact. It ties technical study (ML/DL fundamentals) to real hiring signals like problem-solving, code quality, and experiment logging. The repository’s structure encourages progressive preparation—from fundamentals to mock interviews and post-interview retrospectives. It’s designed to reduce uncertainty and decision fatigue during the often lengthy job-hunt cycle.
    Downloads: 1 This Week
    Last Update:
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  • 4
    Made With ML

    Made With ML

    Learn how to develop, deploy and iterate on production-grade ML

    ...It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets, train models, evaluate performance, and deploy inference services. The repository organizes these concepts into modular Python scripts that follow software engineering best practices such as testing, configuration management, logging, and version control. Through a combination of tutorials, notebooks, and production-ready scripts, the project demonstrates how machine learning applications should be developed as maintainable systems rather than isolated experiments.
    Downloads: 2 This Week
    Last Update:
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  • 5
    Promptify

    Promptify

    se GPT or other prompt based models to get structured output

    Promptify is an open-source Python library designed to simplify prompt engineering and the development of natural language processing pipelines using large language models. The project provides tools that help developers generate structured prompts for different NLP tasks and apply them across multiple generative AI systems. Instead of manually crafting prompts for each task, Promptify introduces a unified architecture that combines prompt templates, language model interfaces, and processing...
    Downloads: 0 This Week
    Last Update:
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