Search Results for "train"
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Showing 58 open source projects for "train"
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PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle
PaddleOCR offers exceptional, multilingual, and practical Optical Character Recognition (OCR) tools that can help users train better models and apply them into practice. Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general ppocr_server series models, and ultra lightweight compression ppocr_mobile_slim series models. ... -
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle... -
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AWS IoT FleetWise Edge
AWS IoT FleetWise Edge Agent
...AWS IoT FleetWise makes it easy and cost-effective for automakers to collect, transform, and transfer vehicle data to the cloud in near-real-time and use it to build applications with analytics and machine learning that improve vehicle quality, safety, and autonomy. Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles. Improve electric vehicle (EV) battery range estimates with crowdsourced environmental data, such as weather and driving conditions, from nearby vehicles. Collect select data from nearby vehicles and use it to notify drivers of changing road conditions, such as lane closures or construction. ... -
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InterpretML
Fit interpretable models. Explain blackbox machine learning
In the beginning, machines learned in darkness, and data scientists struggled in the void to explain them. InterpretML is an open-source package that incorporates state-of-the-art machine-learning interpretability techniques under one roof. With this package, you can train interpretable glass box models and explain black box systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. -
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KeeperRL
A downloadable game for Windows, macOS, and Linux
...You can also play as an adventurer and assault dungeons made by you or other players. You will dig deep into the mountain and build dozens of rooms, corridors and traps. Your minions will train and produce weapons and armor. Prisoners will be tortured. You will research new technologies like alchemy, beast mutation and sorcery. The world is simulated on a very detailed level. Creatures use equipment and consumable items. There are dozens of special items, spells, attributes and special attacks. You can cut off heads and limbs and blind or poison your enemies. -
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Widelands
Widelands is a free, open source real-time strategy game
...As you are not alone in the world, you will meet other clans sooner or later. Some of them may be friendly and you may eventually trade with them. However, if you want to rule the world, you will have to train soldiers and fight. -
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Habitat-Sim
A flexible, high-performance 3D simulator for Embodied AI research
...Determinism and reproducibility are first-class goals, which is critical for benchmarking agents and comparing algorithms. Thanks to its speed and modular design, Habitat-Sim is widely used to prototype embodied agents, train at scale, and evaluate in standardized environments with consistent metrics. -
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qvac-fabric-llm.cpp
QVAC Fabric: cross-platform LLM inference and fine-tuning
...The project focuses on removing hardware limitations traditionally associated with LLM deployment by enabling support for a wide range of backends, including Vulkan, Metal, CUDA, and CPU, making it accessible on devices ranging from smartphones to enterprise servers. It introduces native LoRA fine-tuning capabilities that can be executed directly on consumer hardware, allowing developers to train and adapt models locally without relying on cloud infrastructure. A key innovation is its support for BitNet ternary quantized models, enabling highly efficient inference and training even on resource-constrained systems. -
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dtcltiny - SRCP Model Train Controller
SRCP model train controller
dtcltiny is a small SRCP client to control digital model trains on SRCP systems. dtcltiny needs a SRCP server (e.g. erddcd or srcpd) as hardware link. In cooperation with locking table spdrs60 (http://spdrs60.sourceforge.net/) dtcltiny provides support for train automation. -
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spdrs60 - Digital Model Train Signal Box
Graphical SRCP locking table client
...Visual appearance and usage comply to the original SpDrS60 German Federal Railway company locking table. A SRCP server (e.g. erddcd or srcpd) is needed as a hardware link. In cooperation with train controller dtcltiny (http://dtcltiny.sourceforge.net/) spdrs60 provides support for train automation. -
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Alpaca.cpp
Locally run an Instruction-Tuned Chat-Style LLM
...This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint with a modified script and then quantized with llama.cpp the regular way. -
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Hello AI World
Guide to deploying deep-learning inference networks
...The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. Follow these directions to integrate deep learning into your platform of choice and quickly develop a proof-of-concept design. -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. A sample is specified using 4 columns separated by space (or tabs). -
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fastText
Library for fast text classification and representation
FastText is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices. ext classification is a core problem to many applications, like spam detection, sentiment analysis or smart replies. In this tutorial, we describe how to build a text classifier with the fastText tool. The goal of text classification is to assign documents (such as... -
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StarSpace
Learning embeddings for classification, retrieval and ranking
StarSpace is a general-purpose embedding-based learning framework that trains embeddings for entities (words, sentences, users, items) under various supervision signals (classification, ranking, matching). Instead of focusing on one task, StarSpace supports multi-task and multi-domain setups—for instance, you can train embeddings so that textual queries match item descriptions, sentences map to labels, or users align with liked items in the same embedding space. The training objective is contrastive: for a given query embedding, positive and negative examples are sampled and the model is optimized to score positive higher than negatives. The library supports a variety of tasks (text classification, nearest-neighbor search, recommendation, entity linking) with simple configuration. ... -
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EVEAI is a Deep Learning Library based on python Keras and Tensorflow. EVEAI dll allows embedding inference images from keras models into user-written applications. Under Windows, the EVEAI training Tool provides services to train user specific image datasets and EVEAI dll provides services to existing Windows applications which support inference images. Please visit https://github.com/Hommoner/EVEAI for more information.
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DaNNet
Deep Artificial Neural Network framework using Armadillo
...It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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Keyboard Trainer
Keyboard Trainer, Клавиатурный тренажер
Keyboard trainer for Russian and English. The Standart keyboard use 101 keys. For best practicles you must train the first group in english example : ASDFG, HJK (Enter one or more group in text field); When this group a finished, you can go to next group; You can shufle with numbers or special characters; FIRST GROUP : ASDFGHJKL *** Стандартная клавиатура использует 101 клавишу. Для лучшей практики вы должны тренировать первую группу на русском языке: ФЫВА, ПРОЛДЖЭ (введите одну или несколько групп в текстовом поле); Когда эта группа закончена, вы можете перейти к следующей группе; Вы можете перемешивать с цифрами или специальными символами; ПЕРВАЯ ГРУППА: ФЫВАПРОЛДЖЭ -
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Caffe Framework
Caffe, a fast open framework for deep learning
...Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. -
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kcws
Deep Learning Chinese Word Segment
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... -
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The Edge Machine Learning library
Machine learning algorithms for edge devices
...One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are orders of magnitude lower than other modern ML algorithms. The trained models can be loaded onto edge devices such as IoT devices/sensors, and used to make fast and accurate predictions completely offline. A tool that adapts models trained by above algorithms to be inferred by fixed point arithmetic. -
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MyWords
Personal dictionary for word lovers
My Words is a personal word collection for people who like words. Add, delete, and update words as you collect them. Search through both definitions and spelling. Add your audio comments and train your understanding Written in C++ with QT, should compile on Windows, Linux and Mac. Only Linux has been tested. See wiki for further details -
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Kohonen neural network library is a set of classes and functions for design, train and use Kohonen network (self organizing map) which is one of AI algorithms and useful tool for data mining and discovery knowledge in data (http://knnl.sf.net).
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Armageddon AI
To create a mathematical equation to run a super military grade A.I.
...This project will use trained regression lines to predict the weights of the A.I.'s neurons. Then using the equation's of the regression lines to make an equation for a A.I. that can self train and update its own A.I. equation to out perform humans at completing task. The purpose of this A.I. is to be able to put it into any environment and have it perform better than a human can. -
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WavePacket
Dynamics of quantum systems, controlled by external fields
...The Matlab/Octave version is mature and has been used in production for decades. The C++/Python version has been superseded by https://github.com/ulflor/wavepacket. Using tensor train techniques, the additional WaveTrain package aims at beating the curse of dimensionalit
