Showing 851 open source projects for "python code"

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  • 1
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
    Downloads: 1 This Week
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  • 2
    WaveRNN

    WaveRNN

    WaveRNN Vocoder + TTS

    WaveRNN is a PyTorch implementation of DeepMind’s WaveRNN vocoder, bundled with a Tacotron-style TTS front end to form a complete text-to-speech stack. As a vocoder, WaveRNN models raw audio with a compact recurrent neural network that can generate high-quality waveforms more efficiently than many traditional autoregressive models. The repository includes scripts and code for preprocessing datasets such as LJSpeech, training Tacotron to produce mel spectrograms, training WaveRNN on those...
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  • 3
    AI Atelier

    AI Atelier

    Based on the Disco Diffusion, version of the AI art creation software

    Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a...
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  • 4
    pyprobml

    pyprobml

    Python code for "Probabilistic Machine learning" book by Kevin Murphy

    Python 3 code to reproduce the figures in the books Probabilistic Machine Learning: An Introduction (aka "book 1") and Probabilistic Machine Learning: Advanced Topics (aka "book 2"). The code uses the standard Python libraries, such as numpy, scipy, matplotlib, sklearn, etc. Some of the code (especially in book 2) also uses JAX, and in some parts of book 1, we also use Tensorflow 2 and a little bit of Torch.
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  • 5
    Mask2Former

    Mask2Former

    Code release for "Masked-attention Mask Transformer

    Mask2Former is a unified segmentation architecture that handles semantic, instance, and panoptic segmentation with one model and one training recipe. Its core idea is to cast segmentation as mask classification: a transformer decoder predicts a set of mask queries, each with an associated class score, eliminating the need for task-specific heads. A pixel decoder fuses multi-scale features and feeds masked attention in the transformer so each query focuses computation on its current spatial...
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  • 6
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. ...
    Downloads: 1 This Week
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  • 7
    DeeProtGO

    DeeProtGO

    DeeProtGO is a deep learning model for predicting GO terms of proteins

    This project contains the source code of DeeProtGO as well as an example of its use when predicting GO terms of the biological process sub-ontology for eukaryotic proteins.
    Downloads: 0 This Week
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  • 8
    TensorFlowOnSpark

    TensorFlowOnSpark

    TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters

    By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid.
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  • 9
    LayoutParser

    LayoutParser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

    With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser....
    Downloads: 7 This Week
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  • 10
    The fastai book

    The fastai book

    The fastai book, published as Jupyter Notebooks

    ...These notebooks are used for a MOOC and form the basis of this book, which is currently available for purchase. It does not have the same GPL restrictions that are on this repository. The code in the notebooks and python .py files is covered by the GPL v3 license; see the LICENSE file for details. The remainder (including all markdown cells in the notebooks and other prose) is not licensed for any redistribution or change of format or medium, other than making copies of the notebooks or forking this repo for your own private use. ...
    Downloads: 0 This Week
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  • 11
    RQ-Transformer

    RQ-Transformer

    Implementation of RQ Transformer, autoregressive image generation

    Implementation of RQ Transformer, which proposes a more efficient way of training multi-dimensional sequences autoregressively. This repository will only contain the transformer for now. You can use this vector quantization library for the residual VQ. This type of axial autoregressive transformer should be compatible with memcodes, proposed in NWT. It would likely also work well with multi-headed VQ. I also think there is something deeper going on, and have generalized this to any number of...
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  • 12
    EasyNLP

    EasyNLP

    EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit

    EasyNLP is an easy-to-use NLP development and application toolkit in PyTorch, first released inside Alibaba in 2021. It is built with scalable distributed training strategies and supports a comprehensive suite of NLP algorithms for various NLP applications. EasyNLP integrates knowledge distillation and few-shot learning for landing large pre-trained models, together with various popular multi-modality pre-trained models. It provides a unified framework of model training, inference, and...
    Downloads: 0 This Week
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  • 13
    bert4keras

    bert4keras

    Keras implement of transformers for humans

    Our light reimplementation of bert for keras. A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask...
    Downloads: 0 This Week
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  • 14
    YOLOv3

    YOLOv3

    Object detection architectures and models pretrained on the COCO data

    Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an...
    Downloads: 86 This Week
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  • 15
    CIPS-3D

    CIPS-3D

    3D-aware GANs based on NeRF (arXiv)

    3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator...
    Downloads: 0 This Week
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  • 16
    GLIDE (Text2Im)

    GLIDE (Text2Im)

    GLIDE: a diffusion-based text-conditional image synthesis model

    glide-text2im is an open source implementation of OpenAI’s GLIDE model, which generates photorealistic images from natural language text prompts. It demonstrates how diffusion-based generative models can be conditioned on text to produce highly detailed and coherent visual outputs. The repository provides both model code and pretrained checkpoints, making it possible for researchers and developers to experiment with text-to-image synthesis. GLIDE includes advanced techniques such as...
    Downloads: 0 This Week
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  • 17
    CodeSearchNet

    CodeSearchNet

    Datasets, tools, and benchmarks for representation learning of code

    ...These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets.
    Downloads: 1 This Week
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  • 18
    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: 1 This Week
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  • 19
    GANformer

    GANformer

    Generative Adversarial Transformers

    This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of...
    Downloads: 0 This Week
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  • 20
    e-Dokyumento

    e-Dokyumento

    e-Dokyumento is web-based Document Management System (DMS)

    e-Dokyumento is opensource web-based Document Management System (DMS) A Document Management which automates the basic office document workflow such as receiving, filing, routing, and approving through capturing (scanning), digitizing (OCR Reading), storing, tagging, and electronically routing and approving (e-signature) of electronic documents. # Demo : https://e-dokyumento.herokuapp.com/ https://edokyu.seillig.com/ (refer to Readme.md for the...
    Downloads: 0 This Week
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  • 21
    AWS Step Functions Data Science SDK

    AWS Step Functions Data Science SDK

    For building machine learning (ML) workflows and pipelines on AWS

    The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. ...
    Downloads: 2 This Week
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  • 22
    Ozyr

    Ozyr

    Ozyr is a simple and easy to use OCR snipping tool

    Ozyr is a simple and easy to use OCR snipping tool to get text from images so you can copy and edit it. Source Code: https://github.com/PETEROLO291/Ozyr Installer: 117MB Program: 524MB Version: 1.0
    Downloads: 0 This Week
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  • 23
    Project Alice

    Project Alice

    Main repository of Project Alice, contains main unit source code

    Project Alice is a smart voice home assistant that is completely modular and extensible. It was first built around Snips therefore runs entirely offline and never sends or shares your voice interactions with anyone, Project Alice guarantees your privacy in your home or wherever you’re using Project Alice. However, as an option, since we've built Project Alice on top of Snips, Project Alice can be configured to use some online alternatives and fall backs (for example, using Amazon or Google’s...
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  • 24
    AI Platform Training and Prediction
    AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions. The repository covers the full machine learning lifecycle, including data preprocessing, model...
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  • 25
    Machine Learning Financial Laboratory

    Machine Learning Financial Laboratory

    MlFinLab helps portfolio managers and traders

    ...The library also includes tools for constructing specialized financial data structures, generating predictive features, and evaluating trading strategies through backtesting. Its architecture emphasizes reproducibility, robust testing, and well-documented code so that researchers and practitioners can reliably experiment with financial machine learning models.
    Downloads: 1 This Week
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