Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 67
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The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
MockingBird is an open-source voice cloning and real-time speech generation toolkit that lets you clone a speaker’s voice from a short audio sample (reportedly as little as 5 seconds) and then synthesize arbitrary speech in that voice. It builds on deep-learning based TTS / voice-cloning technology (in the lineage of projects such as Real-Time-Voice-Cloning), but extends it with support for Mandarin Chinese and multiple Chinese speech datasets — broadening its applicability beyond English.... -
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Photonix Photo Manager
A modern, web-based photo management server
...If you don't mind putting up with broken parts or want to help out, run the Docker image and give it a go. I'd love for other contributors to get involved. You can move some photos into the folder data/photos and they should get detected and imported immediately. Once you have finished trying out the system you can edit the volume in the docker-compose.yml file where it says ./data/photos to mount wherever you usually keep photos. System database, thumbnails and other cache data is stored separately from the photos so shouldn't pollute the area. ... -
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scikit-learn tips
50 scikit-learn tips
scikit-learn-tips is an educational repository that collects practical advice and best practices for using the scikit-learn machine learning library effectively. The project consists of short explanations and examples that highlight common patterns, pitfalls, and techniques used when building machine learning workflows in Python. Each tip typically demonstrates how specific components of scikit-learn, such as pipelines, preprocessing utilities, or model evaluation tools, should be applied in... -
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Accelerated Text
Accelerated Text is a no-code natural language generation platform
...It will help you construct document plans which define how your data is converted to textual descriptions. With Accelerated Text you can use such data to generate text for your business reports, your e-commerce platform or your customer support system. Data descriptions require precision. Accelerated Text follows the principle of this strict adherence to data-bound text generation. Via its user interface, it provides instruments to define how the data should be translated into a descriptive text. -
Network Management Software and Tools for Businesses and Organizations | Auvik NetworksReduce IT headaches and save time with a proven solution for automated network discovery, documentation, and performance monitoring. Choose Auvik because you'll see value in minutes, and stay with us to improve your IT for years to come.
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
An implementation of model & data parallel GPT3-like models using the mesh-tensorflow library. If you're just here to play with our pre-trained models, we strongly recommend you try out the HuggingFace Transformer integration. Training and inference is officially supported on TPU and should work on GPU as well. This repository will be (mostly) archived as we move focus to our GPU-specific repo, GPT-NeoX. -
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A Synthetic Data Generator for producing mixed datasets described by relevant, irrelevant, and redundant features.
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Trax
Deep learning with clear code and speed
...Run a pre-trained Transformer, create a translator in a few lines of code. Features and resources, API docs, where to talk to us, how to open an issue and more. Walkthrough, how Trax works, how to make new models and train on your own data. Trax includes basic models (like ResNet, LSTM, Transformer) and RL algorithms (like REINFORCE, A2C, PPO). It is also actively used for research and includes new models like the Reformer and new RL algorithms like AWR. Trax has bindings to a large number of deep learning datasets, including Tensor2Tensor and TensorFlow datasets. You can use Trax either as a library from your own python scripts and notebooks or as a binary from the shell, which can be more convenient for training large models. ... -
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hora
Efficient approximate nearest neighbor search algorithm collections
...Hora implements multiple efficient indexing algorithms that allow systems to rapidly search through high-dimensional vectors produced by machine learning models. These vectors are commonly generated by neural networks to represent images, text, audio, or other data types in a mathematical embedding space. The library is written in Rust and emphasizes performance, safety, and efficient memory management, making it suitable for production-grade applications requiring low latency and high throughput. -
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libfacedetection
Library for face detection in images
.../models/. The file examples/detect-image.cpp and examples/detect-camera.cpp show how to use the library. The library was trained by libfacedetection.train. You can copy the files in directory src/ into your project, and compile them as the other files in your project. The source code is written in standard C/C++. It should be compiled at any platform which supports C/C++. -
Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
...It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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Texthero
Text preprocessing, representation and visualization from zero to hero
Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero. -
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SparrowRecSys
A Deep Learning Recommender System
SparrowRecSys is an open-source deep learning recommendation system framework designed to demonstrate the architecture and implementation of modern industrial-scale recommender systems. The project integrates multiple machine learning models and data processing pipelines to simulate how real-world recommendation platforms operate. It includes components for offline data processing, feature engineering, model training, real-time data updates, and online recommendation services. SparrowRecSys supports a wide range of state-of-the-art recommendation algorithms, including models for click-through rate prediction and user behavior modeling that are widely used in advertising and content recommendation systems. ... -
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Aquila DB
An easy to use Neural Search Engine
...It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies. -
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SneakGAN
StyleGAN2-ADA trained on a dataset of 2000+ sneaker images
StyleGAN2-ADA trained on a dataset of 2000+ sneaker images. This model was inspired by 98mprice's StyleGAN model and uses the same training data. -
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DreamTime
Use artificial intelligence to create images
...Create the body of your dreams, increase or decrease the size of the body parts or leave everything to random. Don't just stay with static photos, you can also create GIFs, MP4 and WEBM videos! Open files or folders from your computer, you can also open files from Instagram and the web. Vitamined with editing tools for any case, you can also make the process fully automatic. Powerful working method that allows you to edit the algorithm step by step and obtain results that only a human could achieve. -
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Parakeet
PAddle PARAllel text-to-speech toolKIT
...In order to facilitate exploiting the existing TTS models directly and developing the new ones, Parakeet selects typical models and provides their reference implementations in PaddlePaddle. Further more, Parakeet abstracts the TTS pipeline and standardizes the procedure of data preprocessing, common module sharing, model configuration, and the process of training and synthesis. The models supported here include Text FrontEnd, end-to-end Acoustic models and Vocoders. -
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gpt-j-api
API for the GPT-J language mode. Including a FastAPI backend
An API to interact with the GPT-J language model and variants! You can use and test the model in two different ways. These are the endpoints of the public API and require no authentication. Just SSH into a TPU VM. This code was tested on both the v2-8 and v3-8 variants. -
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BlazingSQL
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python
...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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Data augmentation
List of useful data augmentation resources
List of useful data augmentation resources. You will find here some links to more or less popular github repos, libraries, papers, and other information. Data augmentation can be simply described as any method that makes our dataset larger. To create more images for example, we could zoom in and save a result, we could change the brightness of the image or rotate it. -
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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tmi.js
Javascript library for the Twitch Messaging Interface
...If the identity has special permission from Twitch for a higher join rate then you should implement your own calls to the client.join method. Disable receiving JOIN/PART events for other users. Good for decreasing network traffic when joining lots of channels or you don't care about this data. After a threshold per channel Twitch stops sending this data so it may not be necessary for all cases. Channels to automatically join upon connecting. The rate of joins is controlled by the options.joinInterval option. Automatically reconnect the client if it gets disconnected for any reason. Sometimes Twitch will request the client to reconnect and tmi.js will disconnect and reconnect even if this option is set to false. -
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Paperless-ng
A supercharged version of paperless, scan, index and archive docs
Paperless is a simple Django application running in two parts, a Consumer (the thing that does the indexing) and a Web server (the part that lets you search & download already-indexed documents). Paper is a nightmare. Environmental issues aside, there’s no excuse for it in the 21st century. It takes up space, collects dust, doesn’t support any form of a search feature, indexing is tedious, it’s heavy and prone to damage & loss. I wrote this to make “going paperless” easier. I do not have to... -
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AI-for-Security-Learning
AI-based security algorithms, and security data analysis
...Topics addressed in the repository include malware detection, anomaly detection, threat classification, and intrusion detection systems. The materials help learners understand how AI can analyze large volumes of security data to identify patterns that may indicate malicious activity. In addition to demonstrating defensive applications, the repository also explores adversarial machine learning concepts that highlight potential vulnerabilities in AI systems. This dual focus allows readers to study both how AI can improve cybersecurity and how machine learning models themselves can become targets of attacks. -
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ML workspace
All-in-one web-based IDE specialized for machine learning
All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. ... -
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DynaQ
Innovative text document search. http://dynaq.opendfki.de for details.
The goal of DynaQ is to develop an inquiry system to explore the personal information space, supporting you with the searching paradigm 'orienteering'. DynaQ is a (desktop)search engine with enhanced functionality for file, email and blog search. Look at our GitLab homepage for sourcecode and documentation: http://dynaq.opendfki.de
