Showing 1407 open source projects for "delphi code source"

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  • 1
    MLRun

    MLRun

    Machine Learning automation and tracking

    MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous...
    Downloads: 1 This Week
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  • 2
    pytorch-cpp

    pytorch-cpp

    C++ Implementation of PyTorch Tutorials for Everyone

    C++ Implementation of PyTorch Tutorials for Everyone. This repository provides tutorial code in C++ for deep learning researchers to learn PyTorch (i.e. Section 1 to 3) Interactive Tutorials are currently running on LibTorch Nightly Version. Libtorch only supports 64bit Windows and an x64 generator needs to be specified. Create all required script module files for pre-learned models/weights during the build. Requires installed python3 with PyTorch and torch-vision. You can choose to only...
    Downloads: 1 This Week
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  • 3
    Llama Cookbook

    Llama Cookbook

    Solve end to end problems using Llama model family

    The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models
    Downloads: 0 This Week
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  • 4
    designlang

    designlang

    Extract any website's complete design system with one command

    designlang is a powerful tool that extracts complete design systems from existing websites using automated analysis and converts them into reusable assets and tokens. It generates structured outputs such as design tokens, semantic components, and styling systems that can be used across multiple platforms. The tool supports exporting to frameworks like Tailwind, SwiftUI, Flutter, and WordPress, making it highly versatile for cross-platform development. It also integrates with tools like Figma...
    Downloads: 2 This Week
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  • 5
    shimmy

    shimmy

    Python-free Rust inference server

    The shimmy project is a lightweight local inference server designed to run large language models with minimal overhead. Written primarily in Rust, the tool provides a small standalone binary that exposes an API compatible with the OpenAI interface, allowing existing applications to interact with local models without significant code changes. This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture...
    Downloads: 2 This Week
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  • 6
    Modelence

    Modelence

    Modelence is an all-in-one TypeScript platform

    Modelence is an all-in-one TypeScript platform aimed at helping teams ship production web apps with far less boilerplate than a typical full-stack setup. It positions itself as a Supabase-style experience tailored toward MongoDB-centric development, bundling common backend needs like authentication, database integration, and observability into a cohesive framework. The project is built to support modern application workflows where product teams want to move quickly without stitching together...
    Downloads: 2 This Week
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  • 7
    Segment Anything

    Segment Anything

    Provides code for running inference with the SegmentAnything Model

    Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A...
    Downloads: 2 This Week
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  • 8
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization). The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding...
    Downloads: 2 This Week
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  • 9
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++...
    Downloads: 2 This Week
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  • 10
    Face Alignment

    Face Alignment

    2D and 3D Face alignment library build using pytorch

    Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively...
    Downloads: 2 This Week
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  • 11
    MCP for Unity

    MCP for Unity

    AI bridge enabling assistants to control and automate Unity Editor

    Unity MCP is an open source integration that connects AI assistants with the Unity Editor through the Model Context Protocol (MCP). It acts as a bridge that allows language models and AI coding tools to interact directly with a Unity development environment using structured commands and tools. By linking an AI assistant to a running Unity project, the system enables automated operations such as managing project assets, modifying scenes, editing scripts, and performing other development tasks...
    Downloads: 2 This Week
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  • 12
    Archon

    Archon

    The knowledge and task management backbone for AI coding assistants

    Archon is an open-source “command center” designed to enhance AI coding assistant workflows by giving developers a centralized environment for knowledge management, context engineering, and task coordination across AI agents. It acts as a backend (including an MCP server) that allows different AI coding tools and assistants to share the same structured context, knowledge base, and task lists, improving consistency, productivity, and collaboration across multi-agent interactions. ...
    Downloads: 1 This Week
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  • 13
    Spark NLP

    Spark NLP

    State of the Art Natural Language Processing

    Experience the power of large language models like never before, unleashing the full potential of Natural Language Processing (NLP) with Spark NLP, the open source library that delivers scalable LLMs. The full code base is open under the Apache 2.0 license, including pre-trained models and pipelines. The only NLP library built natively on Apache Spark. The most widely used NLP library in the enterprise. Spark ML provides a set of machine learning applications that can be built using two main components, estimators and transformers. ...
    Downloads: 1 This Week
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  • 14
    Claude-Flow

    Claude-Flow

    The leading agent orchestration platform for Claude

    Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI...
    Downloads: 3 This Week
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  • 15
    ContextGem

    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.​
    Downloads: 0 This Week
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  • 16
    Simple MCP

    Simple MCP

    A simple TypeScript library for creating MCP servers

    simple-mcp is a TypeScript library designed to facilitate the creation of Model Context Protocol (MCP) servers. It offers a straightforward API, enabling developers to set up MCP servers with minimal code. The library emphasizes type safety through full TypeScript integration and incorporates parameter validation using Zod. It fully implements the MCP, ensuring compatibility with MCP clients. ​
    Downloads: 0 This Week
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  • 17
    Liger Kernel

    Liger Kernel

    Efficient Triton Kernels for LLM Training

    Liger Kernel is a unified kernel developed by LinkedIn to streamline data science and machine learning workflows across different languages and tools. It provides a consistent interface for running code in various languages (such as Python, R, SQL) within a single Jupyter-like environment, enhancing productivity and collaboration for data scientists working in mixed-language projects.
    Downloads: 0 This Week
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  • 18
    Elyra

    Elyra

    Elyra extends JupyterLab with an AI centric approach

    Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page.
    Downloads: 0 This Week
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  • 19
    Reinforcement Learning Course Materials

    Reinforcement Learning Course Materials

    Lecture notes, tutorial tasks including solutions

    Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers).
    Downloads: 0 This Week
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  • 20
    embedchain

    embedchain

    Framework to easily create LLM powered bots over any dataset

    Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds.
    Downloads: 0 This Week
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  • 21
    LangChain for Java

    LangChain for Java

    LangChain4j is an open-source Java library

    LangChain for Java is an open-source Java framework designed to simplify the development of applications powered by large language models. The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build complex AI workflows with minimal boilerplate code.
    Downloads: 1 This Week
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  • 22
    MiniMax-M2

    MiniMax-M2

    MiniMax-M2, a model built for Max coding & agentic workflows

    MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real...
    Downloads: 0 This Week
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  • 23
    files-to-prompt

    files-to-prompt

    Concatenate a directory full of files into a single prompt

    files-to-prompt is a Python command-line tool that takes one or more files or entire directories and concatenates their contents into a single, LLM-friendly prompt. It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It...
    Downloads: 0 This Week
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  • 24
    JMusicBot

    JMusicBot

    A Discord music bot that's easy to set up and run yourself

    ...Supports many sites, including Youtube, Soundcloud, and more. Supports many online radio/streams. Supports local files. Playlist support (both web/youtube and local) This bot (and the source code here) might not be easy to edit for inexperienced programmers. The main purpose of having the source public is to show the capabilities of the libraries, to allow others to understand how the bot works, and to allow those knowledgeable about java, JDA, and Discord bot development to contribute.
    Downloads: 1 This Week
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  • 25
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can...
    Downloads: 0 This Week
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