Showing 4 open source projects for "code new roman"

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  • 1
    diff2html

    diff2html

    Pretty diff to html javascript library (diff2html)

    Each diff provides a comprehensive visualization of the code changes, helping developers identify problems and better understand the changes. Each diff features a line-by-line and side-by-side preview of your changes. All the code changes are syntax highlighted using highlight.js, providing more readability. Similar lines are paired, allowing for easier change tracking. We work hard to make sure you can have your diffs in a simple and flexible way. The AI community building the future....
    Downloads: 1 This Week
    Last Update:
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  • 2
    Milvus Bootcamp

    Milvus Bootcamp

    Dealing with all unstructured data, such as reverse image search

    Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications.
    Downloads: 0 This Week
    Last Update:
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  • 3
    TorchDistill

    TorchDistill

    A coding-free framework built on PyTorch

    torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing...
    Downloads: 6 This Week
    Last Update:
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