Search Results for "s-parameters" - Page 10
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Showing 398 open source projects for "s-parameters"
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. ... -
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Auto-Typer
Hooks your keys to only type the thing you selected
Hooks your keys to only type the thing you selected. Run the command line script. Enter the number of times to repeat the text. Enter wherever to reverse the text or not. Enter what characters the text should contain (Enter for everything). Enter what characters the text should begin with (Enter for everything). Press Windows Shift S and select the area of the text. Press Enter to detect the text. Wait until the program displays the text. Press Enter to start typing. Then start typing, the... -
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FrankMocap
A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator
...It can run frame-by-frame or with temporal smoothing, and includes demo apps for live webcam capture as well as batch processing. Outputs include textured meshes, joint locations, and model parameters that can be exported to common DCC tools and game engines. The codebase offers pretrained models, clear inference scripts, and utilities to visualize results, making single-camera motion capture approachable on commodity hardware. Researchers and creators use it for motion studies, AR/VR prototyping, character animation, and human-in-the-loop editing. -
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CommandlineConfig
A library for users to write configurations in Python
CommandlineConfig is a lightweight Python library designed to simplify managing configuration parameters for experiments and applications, especially in research workflows that require frequent tweaking of hyperparameters. It lets you define configuration in familiar Python dictionaries or JSON files and then access nested parameters via dot notation in code, improving readability and reducing boilerplate. One of its core strengths is the ability to override configuration values directly from the command line, making it convenient to run many experimental variants without editing files repeatedly. ... -
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Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
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Elephas
Distributed Deep learning with Keras & Spark
...Elephas implements a class of data-parallel algorithms on top of Keras, using Spark's RDDs and data frames. Keras Models are initialized on the driver, then serialized and shipped to workers, alongside with data and broadcasted model parameters. Spark workers deserialize the model, train their chunk of data and send their gradients back to the driver. The "master" model on the driver is updated by an optimizer, which takes gradients either synchronously or asynchronously. Hyper-parameter optimization with elephas is based on hyperas, a convenience wrapper for hyperopt and keras. -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
...The project added multi-GPU training, seed settings for reproducible results, adaptive learning rate behavior based on batch size, and both step and cosine learning rate schedules. It also supports Adam and SGD optimizer choices, image cropping, adjustable parameters, and extensive code comments. It is a useful educational and applied repository for users who want to understand or customize YOLOv4 in PyTorch. -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
...The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. It also includes adaptive learning rate adjustment based on batch size, image cropping, many configurable parameters, and expanded comments for easier study. It is well suited for learners and developers who want a hands-on YOLOv3 codebase in PyTorch. -
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Amazon Braket Ocean Plugin
A Python plugin for using Ocean with Amazon Braket
The Amazon Braket Ocean Plugin is an open-source library in Python that provides a framework that you can use to interact with Ocean tools on top of Amazon Braket. Before you begin working with the Amazon Braket Ocean Plugin, make sure that you've installed or configured the following prerequisites. Download and install Python 3.7.2 or greater from Python.org. If you are using Windows, choose Add Python to environment variables before you begin the installation. Make sure that your AWS... -
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Talking Head Anime from a Single Image
Demo for the "Talking Head Anime from a Single Image"
...The system generates animated facial expressions and movements by applying pose transformations to a static image of an anime character. The underlying model uses deep learning techniques to predict how different facial features and body parts should move based on pose parameters or input signals. This allows the software to create realistic animated frames while preserving the identity and appearance of the original character. The repository includes demo applications that allow users to interact with the system through graphical controls or webcam input to drive character motion. These demonstrations illustrate how generative neural rendering can be used to build real-time avatar systems for virtual characters. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
...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 new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. Criterions compute the loss function given the model outputs and targets. ... -
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G2SConverter
Convert models from GoldSource engine to Source engine with AI
...After the Upscaling procedure, the texture is deblured using the Scale-recurrent Network for Deep Image Deblurring. An example of a processed texture is shown in the following image (parameters used: scaling-factor = 4 and deblur iterations = 4) besides upscaling and debluring the utility also generates normal maps for each texture. This is implemented using the DeepBump by HugoTiny model. Examples of normal maps are shown in the following images. -
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ruDALL-E
Generate images from texts. In Russian
...This neural network has been developed and trained by Sber AI researchers in close collaboration with scientists from Artificial Intelligence Research Institute using joined datasets by Sber AI and SberDevices. Russian text-to-image model that generates images from text. The architecture is the same as ruDALL-E XL. Even more parameters in the new version. -
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ELECHEM & FARADAY (Electrochemical)
Simulation tool for electrochemical / electroplating parameters
FARADAY and ELECHEM are the two portable computer programs, find useful for electrochemical researchers, electroplating units, battery as well as supercapacitor industries, process engineers, materials scientists & engineers, electroplaters, hobbyists, and students to evaluate various electrochemical deposition parameters. These computational tools can be used to simulate various electrochemical deposition data or electroplating parameters for metals, alloys, composites as well as energy efficiency of the process. For more information, visit to project Home page: https://www.enote.page/2022/07/computer-simulation-electrochemical.html Designed by: Dr. ... -
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XRD CUBIC
Simulate crystal cell length (a), Miller indices {h, k, l}, d-spacing
This is a basic computer program (coded in Python) to simulate possible unit crystal cell length (a), Miller indices - {h, k, l} and interplanar spacing (d) for cubic crystals from observed (experimental) X-ray diffraction (XRD) angle, 2-theta. It can simulate all these possible crystal lattice parameters for cubic crystal systems between the given 2–theta values within the range of specified cell length (a) limits. 1. Enter wavelength of X-ray (in Angstroms) 2. Enter minimum and maximum diffraction angle as 2-theta (in Degrees) 3. Enter minimum and maximum unit cell length (in Angstroms) All the possible cubic crystal parameters, as well as diffraction angle with reference to d-spacing between the given Miller indices (h k l planes), will be simulated. ... -
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YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5
...Except special cases, we always recommend using our COCO pre-trained weights for initializing the model. As YOLOX is an anchor-free detector with only several hyper-parameters, most of the time good results can be obtained with no changes to the models or training settings. -
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Unet
Source code for unet-pytorch, which can train its own model
...It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. It is useful for developers and students who want a clear U-Net implementation for segmentation experiments, custom masks, and biomedical-style image analysis. -
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csvSearch
A simple Python program to search a csv file
csvSearch is a tiny python program that use a simple gui to search and copy data from a csv (comma separated value) file. All parameters can be provided on the command line, allowing quick launch using specific file and search parameters. -
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Algobot
Cryptocurrency trading bot with a graphical user interface
...For Windows users, it's best to download the .whl package for your Python install and pip install it. For Linux and MacOS users, there's excellent documentation available. Create graphs with real time data and/or moving averages. Run simulations with parameters configured. Run custom backtests with parameters configured. Run live bots with parameters configured. Telegram integration that allows users to trade or view statistics. Create custom, trailing, or limit stop losses. -
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The Fuck
Magnificent app which corrects your previous console command
...It has numerous rules enabled by default, including ones for fixing misspelled commands, fixing wrong commands, spell checking and correcting failed commands, and many, many others. You can also create your own rules and set certain parameters. -
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youtube-dl
Download videos from YouTube (and more sites)
youtube-dl is a command-line program to download videos from YouTube and a few more sites. It requires the Python interpreter (2.6, 2.7, or 3.2+), and it is not platform specific. We also provide a Windows executable that includes Python. youtube-dl should work in your Unix box, in Windows or in Mac OS X. It is released to the public domain, which means you can modify it, redistribute it or use it however you like. youtube-dl is a powerful, open-source command-line program designed to... -
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KeyRandomizer is a simple yet customizable random key generator that can either generate a single key or multiple keys at once. KeyRandomizer also allow you to customize the generation parameters such as how long the key should be and what characters to generate (you can even put your own characters).
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q - Text as Data
Run SQL directly on CSV or TSV files
...Use -e data-encoding to set the input data encoding, -Q query-encoding to set the query encoding, and use -E output-encoding to set the output encoding. Sensible defaults are in place for all three parameters. Files with BOM: Files which contain a BOM (Byte Order Mark) are not properly supported inside python's csv module. q contains a workaround that allows reading UTF8 files which contain a BOM - Use -e utf-8-sig for this. The plan is to separate the BOM handling from the encoding itself, which would allow to support BOMs for all encodings. -
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Lazybee
Create Best Wordlist From Python Tool In Termux
LazyBee is a lightweight Python utility for generating randomized wordlists from an Android Termux environment. Users specify parameters for the generated entries, and the program creates combinations suitable for password-testing datasets or other text-generation tasks. Generated results can be written directly to a text file in the current directory. The program also estimates how long the requested wordlist generation process may take. It is designed to work on both rooted and non-rooted Android devices and uses a simple interactive interface. ... -
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GPT Neo
An implementation of model parallel GPT-2 and GPT-3-style models
...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. NB, while neo can technically run a training step at 200B+ parameters, it is very inefficient at those scales. This, as well as the fact that many GPUs became available to us, among other things, prompted us to move development over to GPT-NeoX. All evaluations were done using our evaluation harness. Some results for GPT-2 and GPT-3 are inconsistent with the values reported in the respective papers. ...
