Search Results for "offline linux dictionary"

MlX offers a local web interface to browse, download, and run ML models via Hugging Face or local sources. It supports searching by tags or tasks, visualization of model metadata, quick inference demos, automatic setup of runtime environments, and works with PyTorch, TensorFlow, and ONNX. Ideal for researchers exploring and testing models via browser.

Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is...

OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference. OpenMLDB is an open-source machine learning database that is committed to solving the data and feature challenges. OpenMLDB has been deployed in hundreds of real-world enterprise applications. It prioritizes the capability of feature engineering using SQL for open-source, which offers a feature platform enabling consistent features for training and...

uTensor is an embedded machine learning inference framework designed to run neural network models on resource-constrained devices such as microcontrollers and Internet-of-Things hardware. The project focuses on enabling TinyML deployments by translating trained machine learning models into efficient C++ code that can execute directly on embedded systems. Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized...

Deep learning chinese word segment. Install the bazel code construction tool and install tensorflow (currently this project requires tf 1.0.0alpha version or above) Switch to the code directory of this project and run ./configure. Compile background service. Pay attention to the public account of waiting for words and reply to kcws to get the corpus download address. Extract the corpus to a directory. Change to the code directory.After installing tensorflow, switch to the kcws code...