Showing 703 open source projects for "oorexx source code"

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  • 1
    BentoML

    BentoML

    Unified Model Serving Framework

    BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference...
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  • 2
    scikit-image

    scikit-image

    Image processing in Python

    scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image builds on scipy.ndimage to provide a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! Read about our mission, vision, and values and how we govern the project. Major proposals...
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  • 3
    DeepSeed

    DeepSeed

    Deep learning optimization library making distributed training easy

    DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU,...
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  • 4
    mergekit

    mergekit

    Tools for merging pretrained large language models

    ...The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code.
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  • 5
    TaskingAI

    TaskingAI

    Open platform for building, deploying, and managing LLM agents

    TaskingAI is an open source platform designed to simplify the development and deployment of applications powered by large language models. It follows a Backend as a Service approach, allowing developers to separate AI logic from frontend product development while maintaining a structured and scalable workflow. TaskingAI integrates hundreds of language models from multiple providers into a unified system, enabling developers to switch models or combine capabilities without major reconfiguration. ...
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  • 6
    Advanced NLP with spaCy

    Advanced NLP with spaCy

    Advanced NLP with spaCy: A free online course

    ...It also demonstrates how spaCy pipelines work and how developers can extend them with custom components and training data. The course is structured as a hands-on learning environment where students can run code examples, experiment with NLP techniques, and build practical language processing applications. Because spaCy is widely used in production environments, the course emphasizes industrial-strength NLP workflows and best practices.
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  • 7
    Dagger

    Dagger

    Containerized automation engine for programmable CI/CD workflows

    Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure.
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  • 8
    seq2seq-couplet

    seq2seq-couplet

    Play couplet with seq2seq model

    ...The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension.
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  • 9
    Lagent

    Lagent

    A lightweight framework for building LLM-based agents

    Lagent is a lightweight open-source framework designed to help developers build autonomous agents powered by large language models. The framework provides tools and abstractions that allow language models to interact with external tools, execute tasks, and perform multi-step reasoning processes. Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with APIs. ...
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  • 10
    NExT-GPT

    NExT-GPT

    Code and models for ICML 2024 paper, NExT-GPT

    NExT-GPT is an open-source research framework that implements an advanced multimodal large language model capable of understanding and generating content across multiple modalities. Unlike traditional models that primarily handle text, NExT-GPT supports input and output combinations involving text, images, video, and audio in a unified architecture. The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different...
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  • 11
    AI Engineering Hub

    AI Engineering Hub

    In-depth tutorials on LLMs, RAGs and real-world AI agent applications

    ...Projects range from OCR applications and local chatbot UIs to multimodal RAG systems and multi-agent automation pipelines, making the hub valuable both as a learning resource and as a practical reference. The repository provides in-depth notebooks, example code, and integration patterns that illustrate how to implement, adapt, and scale AI features in real applications.
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  • 12
    Awesome LLM Apps

    Awesome LLM Apps

    Collection of awesome LLM apps with AI Agents and RAG using OpenAI

    ...The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description, language model dependencies, technology stack notes, and sometimes links to demos or source code, making it easy to explore ideas and reuse concepts for your own projects. Because the landscape of LLM-powered applications changes quickly, the repository is designed to be updated regularly through community contributions, ensuring it stays current with new tools and releases.
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  • 13
    LLM TLDR

    LLM TLDR

    95% token savings. 155x faster queries. 16 languages

    LLM TLDR is a tool that leverages large language models (LLMs) to generate concise, coherent summaries (TL;DRs) of long documents, articles, or text files, helping users quickly understand large amounts of content without reading every word. It integrates with LLM APIs to handle input texts of varying lengths and complexity, applying techniques like chunking, context management, and multi-pass summarization to preserve accuracy even when the source is very large. The system supports both...
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  • 14
    Omnilingual ASR

    Omnilingual ASR

    Omnilingual ASR Open-Source Multilingual SpeechRecognition

    Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new...
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  • 15
    MoCo (Momentum Contrast)

    MoCo (Momentum Contrast)

    Self-supervised visual learning using momentum contrast in PyTorch

    MoCo is an open source PyTorch implementation developed by Facebook AI Research (FAIR) for the papers “Momentum Contrast for Unsupervised Visual Representation Learning” (He et al., 2019) and “Improved Baselines with Momentum Contrastive Learning” (Chen et al., 2020). It introduces Momentum Contrast (MoCo), a scalable approach to self-supervised learning that enables visual representation learning without labeled data. The core idea of MoCo is to maintain a dynamic dictionary with a...
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  • 16
    marimo

    marimo

    A reactive notebook for Python

    marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,...
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  • 17
    Step1X-Edit

    Step1X-Edit

    A SOTA open-source image editing model

    Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the...
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  • 18
    Surya

    Surya

    Implementation of the Surya Foundation Model for Heliophysics

    Surya is an open‑source, AI‑based foundation model for heliophysics developed collaboratively by NASA (via the IMPACT AI team) and IBM. Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture,...
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  • 19
    Klavis AI

    Klavis AI

    MCP integration platforms for AI agents to use tools at any scale

    Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher...
    Downloads: 1 This Week
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  • 20
    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...
    Downloads: 1 This Week
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  • 21
    deepjazz

    deepjazz

    Deep learning driven jazz generation using Keras & Theano

    deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music. The system analyzes musical sequences from an input MIDI file and then generates new musical notes that follow similar stylistic...
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  • 22
    TimesFM

    TimesFM

    Pretrained time-series foundation model developed by Google Research

    TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to...
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  • 23
    Softaworks Agent Skills

    Softaworks Agent Skills

    A curated collection of skills for AI coding agents

    The Softaworks Agent Toolkit is a comprehensive collection of agent skills, commands, and sub-agents designed to augment AI coding assistants like Claude Code, Codex, and Cursor with practical workflow capabilities. It packages broad categories of modular skills that help with development automation, documentation creation, planning, architecture, testing, and soft professional workflows. Beyond simple skills, it also includes agents and CLI slash commands that help developers automate...
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  • 24
    ticket

    ticket

    Fast, powerful, git-native ticket tracking in a single bash script

    ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage...
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  • 25
    Oasis

    Oasis

    Inference script for Oasis 500M

    Open-Oasis provides inference code and released weights for Oasis 500M, an interactive world model that generates gameplay frames conditioned on user keyboard input. Instead of rendering a pre-built game world, the system produces the next visual state via a diffusion-transformer approach, effectively “imagining” the world response to your actions in real time. The project focuses on enabling action-conditional frame generation so developers can experiment with interactive, model-generated...
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