Showing 4736 open source projects for "learning"

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  • 1
    vyper

    vyper

    Pythonic Smart Contract Language for the EVM

    ...See Tools and Resources for an additional list of framework and tools with vyper support. See Documentation for the documentation and overall design goals of the Vyper language. See Learn.Vyperlang.org for learning Vyper by building a Pokémon game. See try.vyperlang.org to use Vyper in a hosted jupyter environment! There is also an online compiler available you can use to experiment with the language and compile to bytecode and/or IR. While the vyper version of the online compiler is updated on a regular basis it might be a bit behind the latest version found in the master branch of this repository.
    Downloads: 2 This Week
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  • 2
    Blockchain Guide

    Blockchain Guide

    Introduce blockchain related technologies, from theory to practice

    ...At present, blockchain technology is still in a stage of rapid development, involving distributed systems, cryptography, game theory, network protocols, and many other disciplines, which bring challenges to both learning and practice. This book hopes to objectively explore the ins and outs of the blockchain concept, analyze key technologies and principles, and use the world's largest open-source distributed ledger project, Hyperledger, as an example to explain specific applications. In the process of developing the Hyperledger project and designing solutions for enterprises, the author has accumulated some practical experience.
    Downloads: 4 This Week
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  • 3
    p5.js

    p5.js

    Client-side JS platform for artists, designers and students to express

    ...We hold events and operate with support from the Processing Foundation. For self-learners and animators, artists, game makers, creative-technologists, curriculum planners, designers, graphic designers, graphics editors, learning experience designers, project managers, software engineer, student, teachers, university faculty members, visualization researchers, etc.
    Downloads: 12 This Week
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  • 4
    Python Tutorial

    Python Tutorial

    Xiaobai Python Tutorial

    ...The course is based on Python 3.10+ and marks newer language features from Python 3.11, 3.12, and 3.13 where relevant. It offers both a document-style reading site and an interactive learning site where users can write code in the browser. The interactive version includes exercises, automatic judging, progress tracking, and unlockable lesson flow. The content covers basic syntax, code style, data types, variables, lists, tuples, dictionaries, sets, loops, functions, iterators, generators, and object-oriented programming.
    Downloads: 3 This Week
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  • 5
    PyOpenCL

    PyOpenCL

    OpenCL integration for Python, plus shiny features

    ...PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and machine learning workflows that demand acceleration.
    Downloads: 3 This Week
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  • 6
    Phi-3-MLX

    Phi-3-MLX

    Phi-3.5 for Mac: Locally-run Vision and Language Models

    Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips.
    Downloads: 3 This Week
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  • 7
    civitai

    civitai

    Open platform for sharing and discovering Stable Diffusion models

    Civitai is an open source project that provides the codebase for a platform designed to share and manage generative AI models used for image generation. It focuses primarily on models compatible with Stable Diffusion and related technologies, allowing creators to upload, organize, and distribute custom AI models and related resources. These resources can include textual inversions, hypernetworks, aesthetic gradients, and variational autoencoders that modify or extend the capabilities of...
    Downloads: 7 This Week
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  • 8
    Qwen-Image-Layered

    Qwen-Image-Layered

    Qwen-Image-Layered: Layered Decomposition for Inherent Editablity

    ...By combining text and structured image representations, it aims to facilitate tasks where both descriptive and structural understanding are important, such as detailed image QA, interactive image editing via prompt layers, and image-conditioned generation with structural control. The layered approach supports training signals that help the model learn how visual elements relate to each other and to textual context, rather than simply learning global image embeddings.
    Downloads: 9 This Week
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  • 9
    AgentENV

    AgentENV

    Distributed platform for running agent environments at scale

    ...Its E2B-compatible HTTP API lets existing Python and TypeScript integrations target a self-hosted deployment with minimal changes. AgentENV is designed for high-density agentic reinforcement learning and currently requires trusted-network deployment because built-in authorization is not yet available.
    Downloads: 5 This Week
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  • 10
    AI Agent Book

    AI Agent Book

    Deep Understanding AI Agents

    ...Ten chapters move from core concepts to context engineering, memory, RAG, knowledge graphs, MCP tools, and coding agents. Later material covers evaluation, supervised fine-tuning, reinforcement learning, self-improvement, multimodal interaction, robotics, and multi-agent cooperation. The repository includes 88 companion experiments, with more than 70 designed to run independently. Readers can access the source chapters, generated figures, code, and downloadable PDF or EPUB editions. Community translations provide versions in several languages alongside the original Chinese text.
    Downloads: 5 This Week
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  • 11
    Anything to NotebookLM

    Anything to NotebookLM

    Multi-source content processor for NotebookLM

    ...The tool can process files locally, extract or transcribe content when needed, and hand the cleaned material to NotebookLM for generation. It is best suited for researchers, students, content curators, and knowledge workers who regularly turn scattered information into organized learning assets.
    Downloads: 5 This Week
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  • 12
    ARIS

    ARIS

    Lightweight Markdown-only skills for autonomous ML research

    ...It also highlights the potential of autonomous agents to handle repetitive or exploratory tasks that would otherwise require significant human effort. The framework is particularly relevant for developers interested in automated experimentation, continuous learning systems, and AI-driven productivity.
    Downloads: 5 This Week
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  • 13
    Lobe Icons

    Lobe Icons

    Brings AI/LLM brand logos to your React & React Native apps

    ...The library includes icons for a wide range of AI providers and models, allowing developers to visually represent integrations with tools such as large language models, AI APIs, and machine learning platforms. These icons are distributed in multiple formats including SVG, PNG, and WebP so they can be used in both web and mobile applications.
    Downloads: 5 This Week
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  • 14
    Megatron-LM

    Megatron-LM

    Ongoing research training transformer models at scale

    Megatron-LM is a GPU-optimized deep learning framework from NVIDIA designed to train extremely large transformer-based language models efficiently at scale. The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and multi-node clusters. ...
    Downloads: 5 This Week
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  • 15
    Antigravity Awesome Skills

    Antigravity Awesome Skills

    The Ultimate Collection of 700+ Agentic Skills for Claude Code

    Antigravity Awesome Skills is a playful yet practical repository that curates a set of clever, expressive, and sometimes whimsical AI agent skill templates designed to help users bootstrap agent behavior quickly. Rather than focusing on production-grade systems, it provides creative and high-impact skills that demonstrate how agents can be used to automate tasks, generate content, assist with daily operations, or integrate into larger workflows with minimal configuration. The project...
    Downloads: 5 This Week
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  • 16
    VibeVoice

    VibeVoice

    Open-source multi-speaker long-form text-to-speech model

    ...The model integrates a Qwen2.5-based large language model with a diffusion head to produce realistic acoustic details and capture conversational context. Training involved curriculum learning with increasing sequence lengths up to 65K tokens, allowing VibeVoice to handle very long dialogues effectively. Safety mechanisms include an audible disclaimer and imperceptible watermarking in all generated audio to mitigate misuse risks.
    Downloads: 11 This Week
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  • 17
    turbovec

    turbovec

    A vector index built on TurboQuant, written in Rust with Python

    ...The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning. TurboVec is useful for developers building retrieval, ranking, semantic search, recommendation, or AI memory systems. Its main value is combining Rust performance with a Python-facing workflow for modern vector search experiments and applications.
    Downloads: 2 This Week
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  • 18
    ANTIRTOS

    ANTIRTOS

    Function pointers queues classes library for Arduino

    ...ANTIRTOS features a basic scheduler, support for cooperative and preemptive multitasking, and offers portability across different CPU architectures with minimal changes. Its simplicity and clarity make it a great starting point for learning real-time systems.
    Downloads: 2 This Week
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  • 19
    PyTorch Lightning

    PyTorch Lightning

    The lightweight PyTorch wrapper for high-performance AI research

    ...PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more!
    Downloads: 8 This Week
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  • 20
    Diplomacy Cicero

    Diplomacy Cicero

    Code for Cicero, an AI agent that plays the game of Diplomacy

    ...It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ...
    Downloads: 0 This Week
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  • 21
    sparklyr

    sparklyr

    R interface for Apache Spark

    sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments.
    Downloads: 1 This Week
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  • 22
    Dask

    Dask

    Parallel computing with task scheduling

    ...It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines.
    Downloads: 1 This Week
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  • 23
    EasyZSwoole

    EasyZSwoole

    swoole, easyswoole, swoole framework

    ...It is born specifically for API and supports the simultaneous monitoring of HTTP, WebSocket, self-defined TCP, UDP protocol, and has rich components, such as collaboration Connect Pool, TP style co-process ORM, co-process microcredit SDK, co-process Kafka client, co-process ElasticSearch client, co-process Consul client, co-process Redis client, co-process Apollo client, co-process NSQ client, co-process self-definition queue、 Many components such as the Memcached client, the co-process view engine, JWT, the co-process RPC, the co-process SMTP client, the co-process HTTP client, the co-process Actor, and the Crontab timer. Let developers write multi-process, step-by-step, and high-available application services with the lowest learning cost and effort.
    Downloads: 0 This Week
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  • 24
    LangKit

    LangKit

    An open-source toolkit for monitoring Language Learning Models (LLMs)

    LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability...
    Downloads: 1 This Week
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  • 25
    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI swift async text to image for SwiftUI app using OpenAI

    ...In machine learning, diffusion models, also known as diffusion probabilistic models, are a class of latent variable models. They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space.
    Downloads: 0 This Week
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