Search Results for "bingo python code" - Page 26
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Showing 2499 open source projects for "bingo python code"
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SeedVR
Repo for SeedVR2 & SeedVR
SeedVR (from the ByteDance-Seed organization) is an open-source research and implementation repository focused on cutting-edge video restoration using diffusion transformer architectures. The project includes both the original SeedVR and its successor SeedVR2 models, which are designed to restore degraded or low-quality video content by learning to reconstruct high-fidelity frames with temporal coherence. These models leverage advanced techniques such as adaptive attention mechanisms and... -
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Web Dev for Beginners
About 24 Lessons, 12 Weeks, Get Started as a Web Developer
Web-Dev-For-Beginners is Microsoft’s open source, project-based curriculum for learning web development from scratch. Designed as a 12-week, 24-lesson course, it covers HTML, CSS, and JavaScript fundamentals through hands-on projects like terrariums, browser extensions, and space games. Each lesson includes a mix of pre-lecture quizzes, written content, assignments, challenges, and post-lecture quizzes to reinforce learning. The course also offers global accessibility with translations in... -
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OmniBox
Collect, organize, use, and share, all in OmniBox
Omnibox (mirror) is a SourceForge mirror of the Omnibox open-source project, which provides a software interface designed to simplify interaction with multiple tools and services through a unified command or search interface. The project focuses on creating a centralized input field where users can enter commands, queries, or shortcuts that trigger actions across different applications or services. Inspired by the omnibox concept used in modern browsers, the system combines search... -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and... -
SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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FullTClash
General proxy performance testing tool based on Clash using Telegram
Back end part useClash project(It can also be called nowmihomo)The relevant code is used as the outing agent. The front end part uses Telegram API as the interactive interface, which needs to be used in conjunction with Telegram, that is, a Telegram robot (bot), FullTClash bot is a Telegram robot (hereinafter referred to as bot) carrying its test tasks. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of... -
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imodelsX
Interpretable prompting and models for NLP
Interpretable prompting and models for NLP (using large language models). Generates a prompt that explains patterns in data (Official) Explain the difference between two distributions. Find a natural-language prompt using input-gradients. Fit a better linear model using an LLM to extract embeddings. Fit better decision trees using an LLM to expand features. Finetune a single linear layer on top of LLM embeddings. Use these just a like a sci-kit-learn model. During training, they fit better... -
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document... -
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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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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You-Get
Dumb downloader that scrapes the web
You-Get is a small command-line utility for downloading media (video, audio and images) from the Web when there are no other means to do so. It can download video and audio files from such popular web sites as YouTube, Twitter, Niconico, Vimeo, Flickr, Instagram and a whole lot more. You-Get is a great option for when you want to enjoy your favorite videos, audio or images from the internet without having to open any web browsers or get interrupted by ads. It’s also a good choice for... -
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cheat.sh
The only cheat sheet you need
...You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. Cheat.sh is intentionally minimal and scriptable, so it fits naturally into shells, CI scripts, editors, and quick lookups without leaving the terminal, while also offering ways to extend or host personal cheat sheets. -
13
Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. -
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CycleGAN and pix2pix in PyTorch
Image-to-Image Translation in PyTorch
...This repo gives developers and researchers a convenient, modern (PyTorch-based) platform to train and test these methods — supporting both paired datasets (input to output) and unpaired datasets (domain-to-domain) with minimal changes. The code supports standard training and inference pipelines, and as of recent updates, compatibility with the latest Python and PyTorch versions (e.g. Python 3.11, PyTorch 2.4) as well as support for distributed/multi-GPU training for scalable workflows. Because of its flexibility, users can apply it to many tasks: e.g. style transfer between domains (e.g. season changes, art-to-photo, etc.), mapping sketches/edges to real images, image colorization, day-to-night, photo enhancement, and more. -
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
...It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale. -
16
Vedo
A python module for scientific analysis of 3D data
A lightweight and powerful python module for scientific analysis and visualization of 3d objects. Inspired by the vpython manifesto "3D programming for ordinary mortals", vedo makes it easy to work with 3D pointclouds, meshes and volumes, in just a few lines of code, even for less experienced programmers. vedo is based on VTK and numpy, with no other dependencies. -
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Tweepy
Twitter for Python
An easy-to-use Python library for accessing the Twitter API. You can also use Git to clone the repository from GitHub to install the latest development version. The easiest way to install the latest version from PyPI is by using pip. Twitter requires all requests to use OAuth for authentication. The API class provides access to the entire twitter RESTful API methods. Each method can accept various parameters and return responses. When we invoke an API method most of the time returned back to... -
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Devon
Open source AI pair programmer for coding, debugging, automation
...It operates as an agent-based system that can explore codebases, edit files, and execute development workflows with minimal manual intervention. Devon uses a client-server architecture with a Python backend and multiple user interfaces, including a terminal interface and an Electron-based desktop application. Devon integrates with multiple large language models, allowing users to choose between different providers for performance, cost, and latency considerations. It is capable of performing tasks such as debugging, writing tests, analyzing code structure, and navigating complex repositories. ... -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation of workflows, PySpur makes it easier to debug interactions between components and identify failures in complex pipelines. ... -
20
ZAPI
ZAPI by Adopt AI is an open-source Python library
ZAPI is a developer-centric API framework that streamlines building, testing, and deploying APIs with strong type safety and minimal boilerplate, helping teams deliver backend services faster with fewer errors. It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication... -
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aisuite
Simple, unified interface to multiple Generative AI providers
Simple, unified interface to multiple Generative AI providers. aisuite makes it easy for developers to use multiple LLM through a standardized interface. Using an interface similar to OpenAI's, aisuite makes it easy to interact with the most popular LLMs and compare the results. It is a thin wrapper around Python client libraries and allows creators to seamlessly swap out and test responses from different LLM providers without changing their code. Today, the library is primarily focused on chat completions. We will expand it to cover more use cases in the near future. Currently supported providers are - OpenAI, Anthropic, Azure, Google, AWS, Groq, Mistral, HuggingFace and Ollama. ... -
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Changelog CI
Changelog CI is a GitHub Action that enables a project
Changelog CI is a GitHub Action that enables a project to automatically generate changelogs. Changelog CI can be triggered on pull_request, workflow_dispatch, and any other events that can provide the required inputs. Changelog CI uses python and GitHub API to generate a changelog for a repository. First, it tries to get the latest release from the repository (If available). Then, it checks all the pull requests/commits merged after the last release using the GitHub API. After that, it... -
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changedetection.io
The best free open source website change detection and restock service
Loved by smart shoppers, data journalists, research engineers, data scientists, security researchers, and more. From simply monitoring website pages that have a change (such as watching prices, and restocking notifications), to deep inspection such as PDF text support, JSON and XML monitoring, and extensive text triggers. Monitor out-of-stock products and get alerts when those products are back in stock, get restock alerts via Discord, Slack, email, and many other platforms. Using the... -
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Mosec
A high-performance ML model serving framework, offers dynamic batching
Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. -
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pre-commit-hooks
Some out-of-the-box hooks for pre-commit
Some out-of-the-box hooks for pre-commit. Using pre-commit-hooks with pre-commit. Instead of loading the files, simply parse them for syntax. A syntax-only check enables extensions and unsafe constructs which would otherwise be forbidden. Using this option removes all guarantees of portability to other yaml implementations. Detect symlinks which are changed to regular files with a content of a path that that symlink was pointing to. This usually happens on Windows when a user clones a...
