Search Results for "multi-valued"
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Showing 52 open source projects for "multi-valued"
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Kivy
Innovative user interfaces made easy
Kivy is an open source, cross-platform UI framework that lets you develop applications that make use of innovative, multi-touch user interfaces. Written in Python with a graphics engine built over OpenGL ES 2, Kivy supports various input devices and protocols, and gives you access to over 20 widgets that are all highly extensible and have built-in multi-touch support. You can run the same codebase on Mac, Windows, Linux, Android and iOS. Kivy is 100% free and open source with a professionally developed and used toolkit, as well as a stable framework and well-documented API, so you can be confident in using it in a commercial product. -
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DouyinLiveRecorder
Live recording software that can be looped and recorded
...The project can send live-status notifications and supports custom scripts around recording events. It runs from source, packaged Windows builds, or Docker, with FFmpeg handling the actual media capture. Its design is aimed at unattended, multi-room recording rather than manual one-stream-at-a-time capture. -
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nature-skills
Skill that conforms to the academic expression and scientific research
...It appears to focus on modularity and interoperability, allowing skills to be combined, extended, or integrated into broader agent ecosystems. The repository is designed to support experimentation with multi-step reasoning, task automation, and contextual tool orchestration for agentic AI systems. By standardizing reusable capabilities, the project helps developers build more maintainable and extensible AI workflows. Overall, nature-skills contributes to the growing ecosystem of modular AI agent tooling and structured automation frameworks. -
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Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
...The project is designed to accelerate cloud adoption by offering opinionated yet flexible patterns aligned with Google Cloud best practices, helping organizations bootstrap their environments quickly while maintaining governance and scalability. It supports complex multi-project and multi-environment setups, making it suitable for large enterprises that require consistent infrastructure provisioning across teams. -
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iptv-api
IPTV live stream source automatic update tool
IPTV API is an automated platform for collecting, validating, testing, filtering, and publishing IPTV stream sources. It aggregates local files and subscriptions, then generates playable results as M3U, TXT, or API output. Users can customize channel templates, aliases, logos, EPG data, protocol preferences, geographic filters, providers, resolution, and speed requirements. The system measures latency, throughput, resolution, and frame rate while removing invalid, unavailable, or repetitive... -
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Antigravity Awesome Skills
The Ultimate Collection of 700+ Agentic Skills for Claude Code
...The project includes skill definitions, example prompts, and usage patterns that highlight how modular abilities can be assembled into functioning assistants. Because it aims to reduce cognitive overhead, many skills show how to structure intents, handle context, and orchestrate multi-step reasoning without deep technical complexity. It also serves as inspiration for users looking to prototype new use cases — from conversational helpers that answer questions to workflow automators that trigger actions. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. -
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DeepSeed
Deep learning optimization library making distributed training easy
...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, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. Sparse attention of DeepSpeed powers an order-of-magnitude longer input sequence and obtains up to 6x faster execution comparing with dense transformers. -
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mimic
Intercept any app, then call it from Python like a library
...Generated clients are ordinary source files built on mimic.App, so developers can inspect and modify them directly. The system can preserve request templates and model multi-step API flows in which one call supplies data for another. Its command-line workflow checks prerequisites, records traffic, lists captured hosts, and prepares reusable sessions. The current documentation focuses on routing iPhone traffic through a Mac-hosted proxy. Mimic is intended for applications and accounts the user is authorized to inspect and automate. -
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colleague-skill
Transform a cold separation into a warm Skill
...It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. It emphasizes communication and coordination, ensuring that agents can contribute meaningfully to shared objectives. This makes it particularly useful for complex projects where multiple perspectives or iterative refinement are needed. -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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VGGT-Ω
[CVPR 2026 Oral] VGGT Omega
...It takes images as input and predicts camera parameters, depth maps, confidence values, and related scene tokens. The project is associated with 3D understanding workflows where models infer scene geometry without a traditional multi-stage reconstruction pipeline. It includes pretrained model variants with different resolutions and text-alignment capabilities, though checkpoint access may require approval. The repository also provides a Gradio demo that can visualize predicted cameras and depth-unprojected point clouds as a GLB scene. VGGT-Omega is best suited for researchers and developers working on 3D reconstruction, visual geometry, and image-based scene understanding. -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of... -
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Flax
Flax is a neural network library for JAX
...The library is widely used in vision, language, and reinforcement learning, often serving as a thin layer atop NumPy-like JAX primitives. Tutorials and examples show patterns for multi-host training, mixed precision, and advanced input pipelines that scale from laptops to TPUs. -
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LangExtract
A Python library for extracting structured information
...LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. The system excels at handling long documents using optimized chunking, multi-pass extraction, and parallel processing to ensure both high recall and structured consistency. -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. ... -
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Music Assistant
Music Assistant is a free, opensource Media library manager
Music Assistant Server is the core backend for Music Assistant, a free and open-source music library manager for local and online music sources. It connects streaming services, local files, metadata providers, and many speaker ecosystems into one centralized music system. The server is designed to run on an always-on device such as a Raspberry Pi, NAS, Intel NUC, or similar home server. It can work as a standalone product, but it is especially tailored for Home Assistant users who want... -
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PyG
Graph Neural Network Library for PyTorch
...It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support, distributed graph learning via Quiver, a large number of common benchmark datasets (based on simple interfaces to create your own), the GraphGym experiment manager, and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. All it takes is 10-20 lines of code to get started with training a GNN model (see the next section for a quick tour). -
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DeepXDE
A library for scientific machine learning & physics-informed learning
...PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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any-llm
Communicate with an LLM provider using a single interface
...It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. The gateway exposes an OpenAI-compatible API, allowing existing tools and workflows to connect without modification. The system emphasizes developer experience with clear error handling, strong typing, and minimal configuration overhead. -
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NanoJev
A nano replica of Jev: parallel decisions, dynamic candidates
NanoJev is an open-source 0.6B-parameter decision model created as a compact reproduction of Jev-style parallel decision making. It takes states and questions as input and returns complete probability distributions without decoding output tokens one by one. The project supports dynamic candidate sets so the available actions can change from one decision to the next. One shared checkpoint has been tested across ViZDoom aiming tasks, maze navigation, and Snake. The repository includes... -
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PyTensor
Python library for defining and optimizing mathematical expressions
PyTensor is a fork of Aesara, a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays. PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. ... -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom... -
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claude-code-transcripts
Tools for publishing transcripts for Claude Code sessions
claude-code-transcripts is a command-line utility that takes session files exported from Claude Code (in JSON or JSONL format) and turns them into clean, navigable HTML transcripts that can be viewed in any modern web browser. It is designed to make the often dense and verbose outputs from AI coding sessions easier to read, share, and archive by breaking conversations into paginated, annotated pages with navigable timelines of prompts and responses. Users can run this tool locally or fetch... -
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EKS Best Practices
A best practices guide for day 2 operations
...Each section dives into operational details—for example, how to manage IAM roles for service accounts, secure the EKS endpoint, handle node auto-scaling, and design for multi-AZ resilience. Because running Kubernetes in production demands many “day-2” considerations (upgrades, drift, monitoring, incident response), the guide provides practical advice beyond simple cluster provisioning.
