Search Results for "website using python" - Page 58
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Showing 2995 open source projects for "website using python"
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IPFS Pinning GitHub Action
Pin your files to IPFS using GitHub Actions
Pin your files to IPFS using GitHub Actions. This GitHub Action helps you to publish your website/assets to IPFS Pinning Services (e.g. Pinata or Firebase using the official IPFS Remote Pinning API. You can use this Action directly from your GitHub workflow. You can find the required credentials on your Pinning Services Website. -
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Transformer TTS
Implementation of a Transformer based neural network
TransformerTTS is an implementation of a non-autoregressive Transformer-based neural network for text-to-speech, built with TensorFlow 2. It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive... -
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Portfolio Jekyll Theme
A minimalist Jekyll theme for building a personal portfolio site
This is a Jekyll theme built using the DevTips Starter Kit as a foundation for starting and following closely the amazing tutorial by Travis Neilson over at DevTips. The purpose of this theme is to provide a clean and simple website for your portfolio. Emphasis is placed on your projects, which are shown front and center on the home page. Everything that you will ever need to know about this Jekyll theme is included in the README, which you can also find in the demo site. -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
...Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data. -
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hebrew-gpt_neo
Hebrew text generation models based on EleutherAI's gpt-neo
Hebrew text generation models based on EleutherAI's gpt-neo. Each was trained on a TPUv3-8 which was made available to me via the TPU Research Cloud Program. The Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture. -
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EH Forwarder Bot
An extensible message tunneling chat bot framework
Codename EH Forwarder Bot (EFB) is an extensible message tunneling chat bot framework that delivers messages to and from multiple platforms and remotely controls your accounts. Since the majority of our channels are using polling for message retrieval, a stable internet connection is necessary for channels to run smoothly. An unstable connection may lead to slow response, or loss of messages. EFB uses a *nix user configuration style, which is described in details in Directories. In short, if... -
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SimCSE
SimCSE: Simple Contrastive Learning of Sentence Embeddings
SimCSE (Simple Contrastive Learning of Sentence Embeddings) is a machine learning framework for training sentence embeddings using contrastive learning. It improves representation learning for NLP tasks. -
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TensorFlow.js models
Pretrained models for TensorFlow.js
...New models should have a test NPM script. You can run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. -
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Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
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Precision_trimmer
Precision resistance value trim circuit using standard parts.
By using standard precision resistors in parallel and series with standard 1, 2, 5 multiple potentiometers, a precision, narrow range resistance trimmer can be created. Fixed resistors are more stable than potentiometers and the circuit reduces the effects of the potentiometer while also determining a precise range. For convenience, a Python script is used to assist in part selection. -
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OpenDrop
An open Apple AirDrop implementation written in Python
OpenDrop is a command-line tool that allows sharing files between devices directly over Wi-Fi. Its unique feature is that it is protocol-compatible with Apple AirDrop which allows to share files with Apple devices running iOS and macOS. Currently (and probably also for the foreseeable future), OpenDrop only supports sending to Apple devices that are discoverable by everybody as the default contacts-only mode requires Apple-signed certificates. We support contacts-only devices by using... -
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GassistPi
Google Assistant for Single Board Computers
Google Assistant for Single Board Computers. In May of 2017, Google Released it’s AIY Projects kit. Initially not many had access to it, so that is when I started modifying the Google Assistant SDK adding AIY like features to help out the ones left without the kit. Every project requires a name and so I named it GassistPi (“G”oogle “Assist”ant on “Pi”). Fast forwarding to date, the project works not only on Pi boards but on a number of other platforms. It has some interesting custom actions... -
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speedtest-cli
Command line interface for testing internet bandwidth using speedtest
Command line interface for testing internet bandwidth using speedtest.net. It is not a goal of this application to be a reliable latency reporting tool. Latency reported by this tool should not be relied on as a value indicative of ICMP style latency. It is a relative value used for determining the lowest latency server for performing the actual speed test against. Speedtest CLI brings the trusted technology and global server network behind Speedtest to the command line. Measure internet... -
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PyBitBanger
Python controlled hardware.
With the demise of the parallel port, a simple way for a Python script to control external hardware has disappeared. The goal of this project is to use relatively simple hardware like an Arduino Nano and the Microchip MCP23S17 port expander as an extensible bit banger. Ideally, all hardware should be leaded and breadboard friendly for easy project prototyping. The ELEGOO Nano is used as an USB RS232 to SPI controller to control the port expander. This fits nicely on a breadboard and has... -
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CoolStore Web Application
A full-stack .NET microservices build on Dapr and Tye
CoolStore Website is a containerized polyglot microservices application consisting of services based on .NET Core, NodeJS, and more running on Service Mesh. It demonstrates how to wire up small microservices and build up a larger application using microservice architectural principles. It's mainly building for the .NET ecosystem with a lot of popular libraries and toolkits that have been used by the .NET community for a long time. -
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Keylogger
A simple keylogger for Windows, Linux and Mac
Keylogger is a simple keystroke logger for Windows, Mac and Linux. A keystroke logger or keylogger is basically a program that records keystrokes and saves them in a log file on your local computer. This keylogger is simple and bare bones, but works wonderfully and is useful for a number of things. You can use it to track key movements and make sure no one is using your computer while you’re away, or use it for self-analysis. In businesses and offices it can be used to monitor employee... -
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DeepSpeech
Open source embedded speech-to-text engine
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the... -
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Big List of Naughty Strings
List of strings which have a high probability of causing issues
The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer... -
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KeexyBox
The box to keep the Internet under your control
KeexyBox allows you to do parental control, block ads, limit telemetry, and browse the Internet anonymously from your home network without installing any software on your devices. It also can be used to create a public wireless access point with the captive portal. It is a software program which requires a Raspberry PI box and which is installed on Raspbian. It constitutes a cut-off point between your devices (computers, tablets, smartphones, etc.) and your router or Internet box.... -
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Couler
Unified Interface for Constructing and Managing Workflows
Couler is a system designed for unified machine learning workflow optimization in the cloud. Couler endeavors to provide a unified interface for constructing and optimizing workflows across various workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow. Couler enhances workflow efficiency through features like Autonomous Workflow Construction, Automatic Artifact Caching Mechanisms, Big Workflow Auto Parallelism Optimization, and Automatic Hyperparameters Tuning. -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and generate visual insights without the need for external GIS software by leveraging interactive widgets and mapping libraries. ... -
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Keepsake
Version control for machine learning
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage. You can get the data back out using the command-line interface or a notebook. -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
DensePose is a computer vision system that maps all human pixels in an RGB image to the 3D surface of a human body model. It extends human pose estimation from predicting joint keypoints to providing dense correspondences between 2D images and a canonical 3D mesh (such as the SMPL model). This enables detailed understanding of human shape, motion, and surface appearance directly from images or videos. The repository includes the DensePose network architecture, training code, pretrained... -
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XLM (Cross-lingual Language Model)
PyTorch original implementation of Cross-lingual Language Model
XLM (Cross-lingual Language Model) is a family of multilingual pretraining methods that align representations across languages to enable strong zero-shot transfer. It popularized objectives like Masked Language Modeling (MLM) across many languages and Translation Language Modeling (TLM) that jointly trains on parallel sentence pairs to tighten cross-lingual alignment. Using a shared subword vocabulary, XLM learns language-agnostic features that work well for classification and sequence... -
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Semantic Segmentation in PyTorch
Semantic segmentation models, datasets & losses implemented in PyTorch
Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero...
