Showing 535 open source projects for "state-thread"

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  • 1
    Kashgari

    Kashgari

    Kashgari is a production-level NLP Transfer learning framework

    Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks.
    Downloads: 0 This Week
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  • 2
    SRU

    SRU

    Training RNNs as Fast as CNNs

    Common recurrent neural architectures scale poorly due to the intrinsic difficulty in parallelizing their state computations. In this work, we propose the Simple Recurrent Unit (SRU), a light recurrent unit that balances model capacity and scalability. SRU is designed to provide expressive recurrence, enable highly parallelized implementation, and comes with careful initialization to facilitate the training of deep models. We demonstrate the effectiveness of SRU on multiple NLP tasks. ...
    Downloads: 0 This Week
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  • 3
    Text Gen

    Text Gen

    Almost state of art text generation library

    Almost state of art text generation library. Text gen is a python library that allow you build a custom text generation model with ease. Something sweet built with Tensorflow and Pytorch(coming soon). Load your data, your data must be in a text format. Download the example data from the example folder. Tune your model to know the best optimizer, activation method to use.
    Downloads: 0 This Week
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  • 4
    CapsGNN

    CapsGNN

    A PyTorch implementation of "Capsule Graph Neural Network"

    ...The high-quality node embeddings learned from the Graph Neural Networks (GNNs) have been applied to a wide range of node-based applications and some of them have achieved state-of-the-art (SOTA) performance. However, when applying node embeddings learned from GNNs to generate graph embeddings, the scalar node representation may not suffice to preserve the node/graph properties efficiently, resulting in sub-optimal graph embeddings. Inspired by the Capsule Neural Network (CapsNet), we propose the Capsule Graph Neural Network (CapsGNN), which adopts the concept of capsules to address the weakness in existing GNN-based graph embeddings algorithms. ...
    Downloads: 0 This Week
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  • 5
    Pension-Calculator

    Pension-Calculator

    A simple retirement benefit calculator app written in python with GUI.

    A simple retirement benefit calculator app written in python with GUI specifically for West Bengal State Govt. employees (India). This app is not associated with Govt. of West Bengal. This app is for informational purpose only. This project is open source under GNU public license v3.0
    Downloads: 0 This Week
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  • 6
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support.
    Downloads: 0 This Week
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  • 7
    TextBrewer

    TextBrewer

    A PyTorch-based knowledge distillation toolkit

    ...It includes various distillation techniques from both NLP and CV field and provides an easy-to-use distillation framework, which allows users to quickly experiment with the state-of-the-art distillation methods to compress the model with a relatively small sacrifice in the performance, increasing the inference speed and reducing the memory usage.
    Downloads: 0 This Week
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  • 8
    Deep Exemplar-based Video Colorization

    Deep Exemplar-based Video Colorization

    The source code of CVPR 2019 paper "Deep Exemplar-based Colorization"

    ...Video frames are colorized in sequence based on the colorization history, and its coherency is further enforced by the temporal consistency loss. All of these components, learned end-to-end, help produce realistic videos with good temporal stability. Experiments show our result is superior to the state-of-the-art methods both quantitatively and qualitatively. In order to colorize your own video, it requires to extract the video frames, and provide a reference image as an example.
    Downloads: 1 This Week
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  • 9
    BasicSR

    BasicSR

    Winning Solution in NTIRE19 Challenges on Video Restoration

    ...The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and Temporal Spatial Attention fusion) that align information across frames and emphasize important features for restoration, enabling state-of-the-art performance on benchmarks such as the REDS challenge. By fusing spatial and temporal context, EDVR produces significantly improved visual quality in restored videos compared with approaches that treat each frame independently.
    Downloads: 0 This Week
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  • 10
    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.
    Downloads: 0 This Week
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  • 11
    Youtube Video Downloader

    Youtube Video Downloader

    Youtube Video Downloader is Open Source GUI tool

    Youtube Video Downloader is Open Source GUI tool to download Youtube video. It is Developed with Python, Qt, and Pytube Library. It is Multi-thread Application. Best Available Option download video in highly available Quality . Download Videos in 720p, 480p, 360p etc.
    Downloads: 1 This Week
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  • 12
    CC-Net

    CC-Net

    Tools to download and cleanup Common Crawl data

    ...The repository documents practical concerns like HTTP failures, snapshot differences, and stats JSONs, reflecting community use across many languages. While powerful, the repo has been archived and is read-only, so users should expect to run it as-is or fork for maintenance. Even in archived state, issues and releases pages remain useful references for implementation details and dataset lineage.
    Downloads: 0 This Week
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  • 13
    3DDFA

    3DDFA

    Fast, accurate and stable 3D dense face alignment

    This work extends 3DDFA, named 3DDFA_V2, titled Towards Fast, Accurate and Stable 3D Dense Face Alignment, accepted by ECCV 2020. The supplementary material is here. The gif above shows a webcam demo of the tracking result, in the scenario of my lab. This repo is the official implementation of 3DDFA_V2. Compared to 3DDFA, 3DDFA_V2 achieves better performance and stability. Besides, 3DDFA_V2 incorporates the fast face detector FaceBoxes instead of Dlib. A simple 3D render written by c++ and...
    Downloads: 3 This Week
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  • 14
    EfficientNet Keras

    EfficientNet Keras

    Implementation of EfficientNet model. Keras and TensorFlow Keras

    This repository contains a Keras (and TensorFlow Keras) reimplementation of EfficientNet, a lightweight convolutional neural network architecture achieving state-of-the-art accuracy with an order of magnitude fewer parameters and FLOPS, on both ImageNet and five other commonly used transfer learning datasets. Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically study model scaling and identify that carefully balancing network depth, width, and resolution can lead to better performance. ...
    Downloads: 0 This Week
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  • 15
    Zipline

    Zipline

    Zipline, a Pythonic algorithmic trading library

    Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python...
    Downloads: 0 This Week
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  • 16
    git-imerge

    git-imerge

    Incremental merge for git

    ...Multiple incremental merges can be in progress at the same time. Each incremental merge has a name, and its progress is recorded in the Git repository as references under refs/imerge/NAME. The current state of an incremental merge can be visualized using the diagram command. An incremental merge can be interrupted and resumed arbitrarily, or even pushed to a server to allow somebody else to work on it.
    Downloads: 0 This Week
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  • 17
    levin

    levin

    in-memory key value server with fuzzy search capabilities

    Levin is an event-based key/value server based on radix-tree (space optimized trie). Key search can be performed with an approximate key matching algorithm based on Levenshtein edit distance.
    Downloads: 0 This Week
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  • 18
    DeText

    DeText

    A Deep Neural Text Understanding Framework

    DeText is a Deep Text understanding framework for NLP-related ranking, classification, and language generation tasks. It leverages semantic matching using deep neural networks to understand member intents in search and recommender systems. As a general NLP framework, DeText can be applied to many tasks, including search & recommendation ranking, multi-class classification and query understanding tasks.
    Downloads: 0 This Week
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  • 19
    Delta ML

    Delta ML

    Deep learning based natural language and speech processing platform

    ...DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users. It helps you to train, develop, and deploy NLP and/or speech models. Use configuration files to easily tune parameters and network structures. What you see in training is what you get in serving: all data processing and features extraction are integrated into a model graph. ...
    Downloads: 0 This Week
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  • 20
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    ...The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions.
    Downloads: 0 This Week
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  • 21
    nginx ui

    nginx ui

    Nginx UI allows you to access and modify the nginx configurations

    ...If you feel the same way I wish you a lot of fun with the application and I am looking forward to your feedback, change requests or even a star. Containerization is now state of the art and therefore the application is delivered in a container. With the menu item Main Config the Nginx specific configuration files can be extracted and updated. These are dynamically read from the Nginx directory. If a file has been added manually, it is immediately integrated into the Nginx UI Main Config menu item.
    Downloads: 0 This Week
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  • 22
    Top Deep Learning Projects

    Top Deep Learning Projects

    A list of popular github projects related to deep learning

    ...By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly discover reputable and well-maintained repositories. This way one can survey state-of-the-art projects, find learning resources, or pick stable libraries for production — without manually sifting through hundreds of repos. The repository is openly licensed under MIT, making it easy to fork, extend, or contribute updates (e.g. adding newer projects or reordering by recent popularity).
    Downloads: 0 This Week
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  • 23
    StellarGraph

    StellarGraph

    Machine Learning on Graphs

    StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes.
    Downloads: 0 This Week
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  • 24
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
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  • 25
    NLP-progress

    NLP-progress

    Repository to track the progress in Natural Language Processing (NLP)

    Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. This document aims to track the progress in Natural Language Processing (NLP) and give an overview of the state-of-the-art (SOTA) across the most common NLP tasks and their corresponding datasets. It aims to cover both traditional and core NLP tasks such as dependency parsing and part-of-speech tagging as well as more recent ones such as reading comprehension and natural language inference. ...
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