Search Results for "neural net python" - Page 9

Showing 582 open source projects for "neural net python"

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  • 1
    ufonet

    ufonet

    UFONet - Denial of Service Toolkit

    UFONet - Is a set of hacktivist tools that allow launching coordinated DDoS and DoS attacks and combine both in a single offensive. It also works as an encrypted DarkNET to publish and receive content by creating a global client/server network based on a direct-connect P2P architecture. + FAQ: https://ufonet.03c8.net/FAQ.html -------------------------------------------- -> UFONet-v1.8 [DPh] "DarK-PhAnT0m!" (.zip) -> md5 = [ c8ab016f6370c8391e2e6f9a7cbe990a ] -> UFONet-v1.8...
    Downloads: 13 This Week
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  • 2
    Email to Event - ETE

    Email to Event - ETE

    The python App/Skrypt automaticly add important events into calendar.

    It is use AI running localy and model you can choose. Skrypt have a tool for automatic add to scheduler. It now not working with Microsoft outlook and Google gmail, for certifications and API polici reasons . Fuly tested on Seznam.cz* services, if you have difrent provier with same type of security it will be working. *Email is using standart IMAP, Calendar use iCalendar API and authentification method. Fast setup: 1. Download and unpack 2. Install LM studio - recomended for GPU...
    Downloads: 0 This Week
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  • 3

    PRMBasic

    Basic script for Python, PHP and .NET

    BASIC dialect for use as generic scripting language for Python, PHP and .NET platform
    Downloads: 0 This Week
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  • 4
    Evolutionary Algorithm

    Evolutionary Algorithm

    Evolutionary Algorithm using Python

    ...Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts.
    Downloads: 0 This Week
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  • 5
    towhee

    towhee

    Framework that is dedicated to making neural data processing

    Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to...
    Downloads: 1 This Week
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  • 6
    Neural Network Intelligence

    Neural Network Intelligence

    AutoML toolkit for automate machine learning lifecycle

    Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'...
    Downloads: 1 This Week
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  • 7
    Parallel WaveGAN

    Parallel WaveGAN

    Unofficial Parallel WaveGAN

    Parallel WaveGAN is an unofficial PyTorch implementation of several state-of-the-art non-autoregressive neural vocoders, centered on Parallel WaveGAN but also including MelGAN, Multiband-MelGAN, HiFi-GAN, and StyleMelGAN. Its main goal is to provide a real-time neural vocoder that can turn mel spectrograms into high-quality speech audio efficiently. The repository is designed to work hand-in-hand with ESPnet-TTS and NVIDIA Tacotron2-style front ends, so you can build complete TTS or singing...
    Downloads: 0 This Week
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  • 8
    Shap-E

    Shap-E

    Generate 3D objects conditioned on text or images

    The shap-e repository provides the official code and model release for Shap-E, a conditional generative model designed to produce 3D assets (implicit functions, meshes, neural radiance fields) from text or image prompts. The model is built with a two-stage architecture: first an encoder that maps existing 3D assets into parameterizations of implicit functions, and then a conditional diffusion model trained on those parameterizations to generate new assets. Because it works at the level of...
    Downloads: 4 This Week
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  • 9
    SoftVC VITS Singing Voice Conversion

    SoftVC VITS Singing Voice Conversion

    SoftVC VITS Singing Voice Conversion

    SoftVC VITS Singing Voice Conversion is a deep learning project focused on singing voice conversion, allowing users to transform one voice into another while preserving melody and timing. Unlike traditional text-to-speech systems, it specializes specifically in singing scenarios and does not provide general TTS functionality. The project leverages neural network architectures derived from VITS and SoftVC research to achieve high-quality voice transformation. It is commonly used in creative...
    Downloads: 0 This Week
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  • 10
    Demucs

    Demucs

    Code for the paper Hybrid Spectrogram and Waveform Source Separation

    Demucs (Deep Extractor for Music Sources) is a deep-learning framework for music source separation—extracting individual instrument or vocal tracks from a mixed audio file. The system is based on a U-Net-like convolutional architecture combined with recurrent and transformer elements to capture both short-term and long-term temporal structure. It processes raw waveforms directly rather than spectrograms, allowing for higher-quality reconstruction and fewer artifacts in separated tracks. The...
    Downloads: 120 This Week
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  • 11
    DALL-E 2 - Pytorch

    DALL-E 2 - Pytorch

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch. The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the text embedding from CLIP. Specifically, this repository will only build out the diffusion prior network, as it is the best performing variant (but which incidentally involves a causal transformer as...
    Downloads: 15 This Week
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  • 12
    PyTorch Implementation of SDE Solvers

    PyTorch Implementation of SDE Solvers

    Differentiable SDE solvers with GPU support and efficient sensitivity

    This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can be...
    Downloads: 0 This Week
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  • 13
    OpenNMT-tf

    OpenNMT-tf

    Neural machine translation and sequence learning using TensorFlow

    OpenNMT is an open-source ecosystem for neural machine translation and neural sequence learning. OpenNMT-tf is a general-purpose sequence learning toolkit using TensorFlow 2. While neural machine translation is the main target task, it has been designed to more generally support sequence-to-sequence mapping, sequence tagging, sequence classification, language modeling. Models are described with code to allow training custom architectures and overriding default behavior. For example, the...
    Downloads: 0 This Week
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  • 14
    ControlNet

    ControlNet

    Let us control diffusion models

    ControlNet is a neural network architecture designed to add conditional control to text-to-image diffusion models. Rather than training from scratch, ControlNet “locks” the weights of a pre-trained diffusion model and introduces a parallel trainable branch that learns additional conditions—like edges, depth maps, segmentation, human pose, scribbles, or other guidance signals. This allows the system to control where and how the model should focus during generation, enabling users to steer...
    Downloads: 2 This Week
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  • 15
    finetuner

    finetuner

    Task-oriented finetuning for better embeddings on neural search

    Fine-tuning is an effective way to improve performance on neural search tasks. However, setting up and performing fine-tuning can be very time-consuming and resource-intensive. Jina AI’s Finetuner makes fine-tuning easier and faster by streamlining the workflow and handling all the complexity and infrastructure in the cloud. With Finetuner, you can easily enhance the performance of pre-trained models, making them production-ready without extensive labeling or expensive hardware. Create...
    Downloads: 0 This Week
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  • 16
    Nougat

    Nougat

    Implementation of Nougat Neural Optical Understanding

    Nougat is a multi-modal generative modeling framework that bridges vision and text modalities with structured generation control (e.g. layout, scene composition) rather than treating images as flat contexts. It combines object-centric modules with transformer-based reasoning to propose, refine, and render scenes in a generative pipeline. The architecture allows you to specify or prompt a layout (which objects should be where) and then the model fills in appearance, context, lighting, and...
    Downloads: 4 This Week
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  • 17
    StoryTeller

    StoryTeller

    Multimodal AI Story Teller, built with Stable Diffusion, GPT, etc.

    ...The final video will be saved as /out/out.mp4, alongside other intermediate images, audio files, and subtitles. For more advanced use cases, you can also directly interface with Story Teller in Python code.
    Downloads: 1 This Week
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  • 18
    DeepH-pack

    DeepH-pack

    Deep neural networks for density functional theory Hamiltonian

    DeepH-pack is the official implementation of the DeepH (Deep Hamiltonian) method described in the paper Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation and in the Research Briefing. DeepH-pack supports DFT results made by ABACUS, OpenMX, FHI-aims or SIESTA and will support HONPAS.
    Downloads: 0 This Week
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  • 19
    Audio Webui

    Audio Webui

    A webui for different audio related Neural Networks

    Audio Webui is a Gradio-based web user interface that unifies a wide range of audio-related neural networks under a single, accessible front end. It is designed as an “all-in-one” environment where users can experiment with text-to-speech, voice cloning, generative music, and other neural audio models without writing boilerplate code. The project supports multiple back-end models and toolchains (such as Bark, RVC, AudioLDM, Audiocraft, and other text-to-audio or voice-cloning tools),...
    Downloads: 0 This Week
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  • 20
    AI Upscaler for Blender

    AI Upscaler for Blender

    AI Upscaler for Blender using Real-ESRGAN

    Blender add-on to dramatically reduce render times using the Real-ESRGAN upscaler. Rendering an HD image in Blender takes 37 minutes. Upscaling can render a similar quality image in 5 mins total. Any PC or laptop can now do 3D rendering. 4k images can be rendered in the time it would take to render HD 1080p images. HD 1080p images can be rendered in record time on low-end hardware. Installation is easy. Just install the addon. No special hardware or GPU is required. Upscaling is done...
    Downloads: 0 This Week
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  • 21
    Prime QA

    Prime QA

    State-of-the-art Multilingual Question Answering research

    PrimeQA is a public open source repository that enables researchers and developers to train state-of-the-art models for question answering (QA). By using PrimeQA, a researcher can replicate the experiments outlined in a paper published in the latest NLP conference while also enjoying the capability to download pre-trained models (from an online repository) and run them on their own custom data. PrimeQA is built on top of the Transformers toolkit and uses datasets and models that are directly...
    Downloads: 0 This Week
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  • 22

    Wicogen-windows-icon-generator

    Windows folder icon generator

    Wicogen Easily Customize your folders and make Windows suite to your taste! Just choose an image and it will be automatically applied to a folder of your choice! Quickly search the net for images you like by a folder name and a search term! Supported sources for online search: Google images Bing images IMDB (covers for movies and TV shows) MyAnimeList.net (covers for anime and movies) For Movie/TV, I recommend the disk style available in the "Style:" drop-down. If you find all...
    Downloads: 0 This Week
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  • 23
    hloc

    hloc

    Visual localization made easy with hloc

    This is hloc, a modular toolbox for state-of-the-art 6-DoF visual localization. It implements Hierarchical Localization, leveraging image retrieval and feature matching, and is fast, accurate, and scalable. This codebase won the indoor/outdoor localization challenges at CVPR 2020 and ECCV 2020, in combination with SuperGlue, our graph neural network for feature matching. We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using...
    Downloads: 0 This Week
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  • 24
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs.
    Downloads: 0 This Week
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  • 25
    fastMRI

    fastMRI

    A large open dataset + tools to speed up MRI scans using ML

    fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data...
    Downloads: 0 This Week
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