Showing 312 open source projects for "tiny-core-plus"

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    Host LLMs in Production With On-Demand GPUs

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  • 1
    learn-machine-learning-in-two-months

    learn-machine-learning-in-two-months

    Essential Knowledge for learning Machine Learning in two months

    The learn-machine-learning-in-two-months repository is an educational open-source project designed to guide beginners through the process of learning machine learning and deep learning concepts within a structured two-month study plan. The project compiles curated resources, tutorials, and practical notebooks that introduce fundamental topics such as mathematics for machine learning, Python programming, and essential libraries like NumPy and TensorFlow. It progressively moves from...
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  • 2
    Python ML Jupyter Notebooks

    Python ML Jupyter Notebooks

    Practice and tutorial-style notebooks

    Python ML Jupyter Notebooks is an educational repository that demonstrates how to implement machine learning algorithms and data science workflows using Python. The project provides numerous examples and tutorials covering classical machine learning techniques such as regression, classification, clustering, and dimensionality reduction. It includes code implementations that show how to build models using popular libraries like scikit-learn, NumPy, pandas, and Matplotlib. The repository is...
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  • 3
    Coqui STT

    Coqui STT

    The deep learning toolkit for speech-to-text

    Coqui STT is a fast, open-source, multi-platform, deep-learning toolkit for training and deploying speech-to-text models. Coqui STT is battle-tested in both production and research. Multiple possible transcripts, each with an associated confidence score. Experience the immediacy of script-to-performance. With Coqui text-to-speech, production times go from months to minutes. With Coqui, the post is a pleasure. Effortlessly clone the voices of your talent and have the clone handle the problems...
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  • 4
    AirSim

    AirSim

    A simulator for drones, cars and more, built on Unreal Engine

    AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a...
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  • 5
    Hello AI World

    Hello AI World

    Guide to deploying deep-learning inference networks

    Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. 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...
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  • 6
    pyntcloud

    pyntcloud

    pyntcloud is a Python library for working with 3D point clouds

    This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and...
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  • 7
    WaveFunctionCollapse

    WaveFunctionCollapse

    Bitmap & tilemap generation from a single example

    This program generates bitmaps that are locally similar to the input bitmap. WFC initializes output bitmap in a completely unobserved state, where each pixel value is in superposition of colors of the input bitmap (so if the input was black & white then the unobserved states are shown in different shades of grey). The coefficients in these superpositions are real numbers, not complex numbers, so it doesn't do the actual quantum mechanics, but it was inspired by QM. Then the program goes into...
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  • 8
    Flashlight library

    Flashlight library

    A C++ standalone library for machine learning

    Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across multiple domains. Flashlight can be broken down into several components as described above. Each component can be incrementally built by specifying the correct build options. ...
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  • 9
    ML++

    ML++

    A library created to revitalize C++ as a machine learning front end

    Machine learning is a vast and exiciting discipline, garnering attention from specialists of many fields. Unfortunately, for C++ programmers and enthusiasts, there appears to be a lack of support in the field of machine learning. To fill that void and give C++ a true foothold in the ML sphere, this library was written. The intent with this library is for it to act as a crossroad between low-level developers and machine learning engineers. ML++, like most frameworks, is dynamic, and...
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  • 10
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    ...Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
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  • 11
    TorchGAN

    TorchGAN

    Research Framework for easy and efficient training of GANs

    The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to provide building blocks for popular GANs and also to allow customization for cutting-edge research. ...
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  • 12
    TensorRT Pro

    TensorRT Pro

    C++ library based on tensorrt integration

    High-level interface for C++/Python. Simplify the implementation of the custom plugin. And serialization and deserialization have been encapsulated for easier usage. Simplify the compilation of fp32, fp16 and int8 for facilitating the deployment with C++/Python in server or embedded device. Models ready for use also with examples are RetinaFace, Scrfd, YoloV5, YoloX, Arcface, AlphaPose, CenterNet and DeepSORT(C++).
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  • 13
    BlazingSQL

    BlazingSQL

    BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python

    BlazingSQL is a GPU-accelerated SQL engine built on top of the RAPIDS ecosystem. RAPIDS is based on the Apache Arrow columnar memory format, and cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data. BlazingSQL is a SQL interface for cuDF, with various features to support large-scale data science workflows and enterprise datasets.
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  • 14
    Sklearn TensorFlow

    Sklearn TensorFlow

    Sklearn and TensorFlow: A Practical Guide to Machine Learning

    ...The repository organizes the content as structured documentation that can be compiled into multiple formats such as HTML, PDF, EPUB, and MOBI, allowing users to read the material both online and offline. It focuses on teaching core machine learning concepts using Python while demonstrating practical workflows with popular libraries like Scikit-Learn and TensorFlow. The material covers topics ranging from basic machine learning theory to deep learning techniques and model evaluation, enabling learners to build and experiment with models step by step.
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  • 15
    YOLOv4-large

    YOLOv4-large

    Scaled-YOLOv4: Scaling Cross Stage Partial Network

    ...This scaling strategy enables the model to adapt to different hardware environments while maintaining a strong balance between speed and detection accuracy. The repository includes multiple model variants such as YOLOv4-tiny, YOLOv4-CSP, and large-scale configurations designed for high-performance detection tasks.
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  • 16
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    ...We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. Task driven implementation with dynamic model and dataset resolution from arguments. Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. Each base class supports a different data format.
    Downloads: 1 This Week
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  • 17
    YOLO ROS

    YOLO ROS

    YOLO ROS: Real-Time Object Detection for ROS

    ...The YOLO packages have been tested under ROS Noetic and Ubuntu 20.04. We also provide branches that work under ROS Melodic, ROS Foxy and ROS2. Darknet on the CPU is fast (approximately 1.5 seconds on an Intel Core i7-6700HQ CPU @ 2.60GHz × 8) but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. The CMakeLists.txt file automatically detects if you have CUDA installed or not. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia.
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  • 18
    TNN

    TNN

    Uniform deep learning inference framework for mobile

    TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's...
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  • 19
    Machine Learning Beginner

    Machine Learning Beginner

    Machine Learning Beginner Public Account Works

    Machine Learning Beginner targets newcomers who are just getting started with machine learning and need a gentle, guided path. It introduces the core vocabulary and the mental map of supervised and unsupervised learning before moving into simple algorithms. The materials prioritize conceptual clarity, then progressively add code to solidify understanding. Step-by-step examples help learners see how data preparation, model training, evaluation, and iteration fit together. Because the scope is intentionally beginner-friendly, it’s an approachable springboard to more advanced resources. ...
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  • 20
    Machine-Learning-Notes

    Machine-Learning-Notes

    Zhou Zhihua's "Machine Learning" push notes

    The Machine-Learning-Notes repository contains detailed handwritten-style study notes based on the popular machine learning textbook by Zhou Zhihua. The project focuses on deriving formulas and explaining algorithms step by step so that learners can understand the mathematical foundations behind machine learning methods. The notes span sixteen chapters that cover a wide range of topics, including model evaluation, linear models, decision trees, neural networks, support vector machines,...
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  • 21
    PaddlePaddle models

    PaddlePaddle models

    Pre-trained and Reproduced Deep Learning Models

    Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,...
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  • 22
    OpenPose

    OpenPose

    Real-time multi-person keypoint detection library for body, face, etc.

    OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or...
    Downloads: 21 This Week
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  • 23
    Surface Defect Detection Dataset Papers

    Surface Defect Detection Dataset Papers

    Constantly summarizing open source dataset and critical papers

    At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery manufacturing, semiconductors and electronics, chemical, pharmaceutical, aerospace, light industry and other industries. Traditional surface defect detection methods based on machine vision often use conventional image processing algorithms or artificially designed features plus classifiers. Generally speaking, imaging schemes are usually designed by using the different properties of the inspected surface or defects. A reasonable imaging scheme helps to obtain images with uniform illumination and clearly reflect the surface defects of the object. In recent years, many defect detection methods based on deep learning have also been widely used in various industrial scenarios.
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  • 24
    Libra

    Libra

    Ergonomic machine learning for everyone

    An ergonomic machine learning library for non-technical users. Save time. Blaze through ML.
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  • 25
    NLP Architect

    NLP Architect

    A model library for exploring state-of-the-art deep learning

    NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a...
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