Search Results for "artificial intelligence" - Page 7
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Showing 809 open source projects for "artificial intelligence"
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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APIPark
APIPark is the #1 open-source AI Gateway and Developer Portal
APIPark is an open-source, all-in-one AI gateway and API developer portal, that helps developers and enterprises easily manage, integrate, and deploy AI services. No matter which AI model you use, APIPark provides a one-stop integration solution. It unifies the management of all authentication information and tracks the costs of API calls. Standardize the request data format for all AI models. When switching AI models or modifying prompts, it won’t affect your app or microservices,... -
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Tiny CUDA Neural Networks
Lightning fast C++/CUDA neural network framework
This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared... -
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diff2html
Pretty diff to html javascript library (diff2html)
Each diff provides a comprehensive visualization of the code changes, helping developers identify problems and better understand the changes. Each diff features a line-by-line and side-by-side preview of your changes. All the code changes are syntax highlighted using highlight.js, providing more readability. Similar lines are paired, allowing for easier change tracking. We work hard to make sure you can have your diffs in a simple and flexible way. The AI community building the future.... -
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Opacus
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,... -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via... -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is... -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research... -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,... -
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Sourcery AI Code Review
Instant AI code reviews
Sourcery is an AI-powered code assistant designed to help developers write cleaner, more maintainable Python code by suggesting real-time refactorings, improvements, and best-practice rewrites directly in popular editors and IDEs. Instead of just offering autocomplete, Sourcery analyzes existing functions and code patterns to provide context-aware suggestions that can simplify logic, reduce duplication, improve naming, and correct anti-patterns, helping developers adhere to idiomatic style... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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DocsGPT
Private AI platform for agents, enterprise search and RAG pipelines
DocsGPT is an open-source AI platform for deploying private RAG pipelines, AI agents, and enterprise search on your own infrastructure. Connect any data source (PDFs, DOCX, CSV, Excel, HTML, audio, GitHub, databases, URLs) and get accurate, hallucination-free answers with source citations. Choose your LLM: OpenAI, Anthropic, Google Gemini, or local models. Works with Qdrant, MongoDB, and Elasticsearch and more. Deploy via Docker or Kubernetes with full data sovereignty. Build... -
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Groq TypeScript / Node.s
The official Node.js / Typescript library for the Groq API
Groq TypeScript / Node.s (also often referred to as “groq-sdk” on npm) is the official Node.js / TypeScript client library for Groq’s REST API, enabling JavaScript/TypeScript developers to integrate LLM and AI-powered services into web backends, serverless functions, or frontend apps. It exports strongly-typed interfaces for models, chat completions, file uploads (e.g. for audio transcription), and other endpoints, allowing for better type safety and developer experience when using Groq from... -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and... -
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AI Commits
A CLI that writes your git commit messages for you with AI
AI Commits is a command-line tool that writes your git commit messages for you using an AI model. It works by running git diff to gather your staged code changes, sending that diff to an LLM (originally GPT-3, now configurable), and receiving back a concise, human-readable commit message. The tool is designed to integrate cleanly into a developer’s workflow so that generating a descriptive commit message becomes a single command rather than a chore. It supports configuration via environment... -
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Claude Platform CLI
The CLI for the Claude API
Claude Platform CLI is a command-line tool that lets users interact directly with the Anthropic Claude API from their terminal. It provides access to API resources through structured subcommands, making it useful for both interactive exploration and automated workflows. The CLI simplifies API requests by supporting typed flags, piped YAML or JSON input, and inline file references instead of manually writing complex JSON. Users can format, filter, and transform responses directly in the... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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Courses (Anthropic)
Anthropic's educational courses
Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured... -
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ARC-AGI
The Abstraction and Reasoning Corpus
ARC-AGI is a benchmark dataset and experimental framework designed to evaluate and advance artificial general intelligence by testing systems on abstract reasoning tasks that require human-like problem-solving abilities. It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. The dataset is structured as grid-based puzzles, where each task requires understanding transformations such as symmetry, counting, or spatial manipulation. ... -
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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... -
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ant CLI
ant CLI - Command line tool for Anthropic Claude API
The ant CLI is a command-line tool that lets users interact directly with the Claude API from their terminal. It exposes every API resource as a structured subcommand, making it useful for both hands-on exploration and automated workflows. The ant CLI simplifies API requests by allowing users to build request bodies with typed flags, piped YAML or JSON, stdin input, and inline file references instead of manually writing complex JSON. It also includes built-in output formatting, response... -
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Starter Applets
Google AI Studio Starter Apps
starter-applets is a collection of minimal, sandboxed example “applets” that demonstrate how to compose Gemini-powered microapps (chat widgets, image generation, workflows) that can be embedded in other applications or used standalone. The applets are structured with a focus on simplicity: each presents a prompt input, minimal UI logic, and inline display of the resulting output or widget (e.g. generated text, images). They are built to illustrate best practices (e.g. safety guards, prompt...
