Search Results for "oorexx source code" - Page 30

Showing 2291 open source projects for "oorexx source code"

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  • 1
    Tweepy

    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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  • 2
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
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  • 3
    Pelican

    Pelican

    Static site generator that supports Markdown and reST syntax

    Pelican is a static site generator that requires no database or server-side logic. Chronological content (e.g., articles, blog posts) as well as static pages. Integration with external services. Site themes (created using Jinja2 templates). Publication of articles in multiple languages. Generation of Atom and RSS feeds. Code syntax highlighting via Pygments. Import existing content from WordPress, Dotclear, or RSS feeds. Fast rebuild times due to content caching and selective output writing....
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  • 4
    1D Visual Tokenization and Generation

    1D Visual Tokenization and Generation

    This repo contains the code for 1D tokenizer and generator

    The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact...
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  • 5
    UNO

    UNO

    A Universal Customization Method for Single and Multi Conditioning

    UNO is a project by ByteDance introduced in 2025, titled “A Universal Customization Method for Both Single and Multi-Subject Conditioning.” It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is...
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  • 6
    Sa2VA

    Sa2VA

    Official Repo For "Sa2VA: Marrying SAM2 with LLaVA

    Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about...
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  • 7
    PythonPark

    PythonPark

    Python open source project "The Road to Self-Study Programming"

    PythonPark is a large, curated “learning playground” for Python — essentially a comprehensive self-study meta-repository aimed at helping learners progress in Python programming, data science, machine learning, web scraping, and software engineering practices. It aggregates tutorials, learning guides, project examples, and resources across topics: from Python basics and data structures to machine learning, web scraping, and even interview preparation and “programmer life” guidance. Because...
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  • 8
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 9
    PaSa

    PaSa

    An advanced paper search agent powered by large language models

    PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand...
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  • 10
    Step-Audio-EditX

    Step-Audio-EditX

    LLM-based Reinforcement Learning audio edit model

    Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level...
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  • 11
    shot-scraper

    shot-scraper

    A command-line utility for taking automated screenshots of websites

    shot-scraper is a command-line utility for taking automated screenshots of web pages using a headless browser engine. After installation, a single command can capture a full-page screenshot of a URL and save it to a file, making it ideal for documentation, monitoring, and visual regression tasks. Under the hood it uses a modern browser (installed via a one-time shot-scraper install step) and exposes options for viewport size, full-page versus clipped screenshots, and device emulation. Beyond...
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  • 12
    Norfair

    Norfair

    Lightweight Python library for adding real-time multi-object tracking

    Norfair is a customizable lightweight Python library for real-time multi-object tracking. Using Norfair, you can add tracking capabilities to any detector with just a few lines of code. Any detector expressing its detections as a series of (x, y) coordinates can be used with Norfair. This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. At the same time, it is...
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  • 13
    CleanVision

    CleanVision

    Automatically find issues in image datasets

    CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used...
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  • 14
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust...
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  • 15
    git-delete-merged-branches

    git-delete-merged-branches

    Command-line tool to delete merged Git branches

    A convenient command-line tool helping you keep repositories clean. Supports deletion of both local and remote branches. Detects multiple forms of de-facto merges (rebase merges, squash merges (needs --effort=3), single or range cherry-picks… leveraging git cherry). Supports workflows with multiple release branches, e.g. only delete branches that have been merged to all of master, dev and staging. Quick interactive configuration. Provider agnostic: Works with GitHub, GitLab, Gitea and any...
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  • 16
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement...
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  • 17
    Poetiq

    Poetiq

    Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1

    poetiq-arc-agi-solver is the open-source codebase from Poetiq that replicates their record-breaking submission to the challenging benchmark suite ARC-AGI (both ARC-AGI-1 and ARC-AGI-2). The project demonstrates a system that orchestrates large language models (LLMs) — like those from major providers — with carefully engineered prompting, reasoning workflows, and dynamic strategies, to tackle the abstract, logic-heavy problems in ARC-AGI. Instead of relying on a single prompt or fixed...
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  • 18
    GLM-4.6V

    GLM-4.6V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    GLM-4.6V represents the latest generation of the GLM-V family and marks a major step forward in multimodal AI by combining advanced vision-language understanding with native “tool-call” capabilities, long-context reasoning, and strong generalization across domains. Unlike many vision-language models that treat images and text separately or require intermediate conversions, GLM-4.6V allows inputs such as images, screenshots or document pages directly as part of its reasoning pipeline — and...
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  • 19
    FlowLens MCP

    FlowLens MCP

    Open-source MCP server that gives your coding agent

    FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console logs, DOM events, storage changes, and more, and exports it. ...
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  • 20
    mlforecast

    mlforecast

    Scalable machine learning for time series forecasting

    mlforecast is a time-series forecasting framework built around machine-learning models, designed to make forecasting both efficient and scalable. It lets you apply any regressor that follows the typical scikit-learn API, for example, gradient-boosted trees or linear models, to time-series data by automating much of the messy feature engineering and data preparation. Instead of writing custom code to build lagged features, rolling statistics, and date-based predictors, mlforecast generates...
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  • 21
    PyTorch-Tutorial-2nd

    PyTorch-Tutorial-2nd

    CV, NLP, LLM project applications, and advanced engineering deployment

    PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization strategies. ...
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  • 22
    Swirl

    Swirl

    Swirl queries any number of data sources with APIs

    Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank...
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  • 23
    uvicorn-gunicorn-fastapi

    uvicorn-gunicorn-fastapi

    Docker image with Uvicorn managed by Gunicorn

    Docker image with Uvicorn managed by Gunicorn for high-performance FastAPI web applications in Python with performance auto-tuning. Optionally with Alpine Linux.
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  • 24
    AIConfig

    AIConfig

    AIConfig is a config-based framework to build generative AI apps

    AIConfig is an open-source framework designed to simplify the development and management of generative AI applications by separating AI logic from application code. The framework allows prompts, model configurations, and parameters to be stored as structured configuration files that can be version controlled and managed independently from the rest of the software system.
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  • 25
    GitGot

    GitGot

    Semi-automated tool for discovering exposed secrets in GitHub data

    GitGot is an open source security tool designed to help users quickly search large amounts of public data on GitHub to identify potentially exposed secrets. It operates as a semi-automated, feedback-driven system that combines automated search capabilities with human guidance to refine results during investigation. GitGot leverages the GitHub Search API to perform queries across repositories, files, and gists, allowing security researchers and penetration testers to discover sensitive information that may have been unintentionally exposed in public code. ...
    Downloads: 4 This Week
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