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Showing 216 open source projects for "top"
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Scholar
Traditional machine learning on top of Nx
Traditional machine learning tools built on top of Nx. Scholar implements several algorithms for classification, regression, clustering, dimensionality reduction, metrics, and preprocessing. -
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Botonic
Build chatbots and conversational experiences using React
Botonic is a full-stack Javascript framework to create chatbots and modern conversational apps that work on multiple platforms, web, mobile and messaging apps (Messenger, Whatsapp, Telegram, etc). Building modern applications on top of messaging apps like Whatsapp or Messenger is much more than creating simple text-based chatbots. Botonic is a full-stack serverless framework that combines the power of React and Tensorflow.js to create amazing experiences at the intersection of text and graphical interfaces. With Botonic you can focus on creating the best conversational experience for your users instead of dealing with different messaging APIs, AI/NLP complexity or managing and scaling infrastructure. ... -
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DramaBox
super expressive prompting model based on ltx2.3
DramaBox is an expressive text-to-speech and voice cloning project from Resemble AI built on top of the LTX-2.3 audio branch. It generates speech from prompts that control not only the spoken text, but also speaker identity, emotion, delivery style, laughs, sighs, pauses, and transitions. Users can optionally provide a voice reference of around 10 seconds or more to clone the target timbre while still guiding performance through scene-style prompting. -
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fugue
A unified interface for distributed computing
Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites. -
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Unsloth Studio
Unified web UI for training and running open models locally
Unsloth Studio is a web-based interface for running and training AI models locally with a unified and user-friendly experience. It allows users to work with a wide range of models for text, audio, vision, embeddings, and more without relying heavily on cloud infrastructure. Built on top of the Unsloth framework, it focuses on high-performance training with reduced VRAM usage and faster speeds compared to traditional methods. The platform supports fine-tuning, pretraining, and reinforcement learning workflows, making it suitable for both experimentation and production use. Users can interact with models through chat, upload files like PDFs or images, and execute code within the environment to improve outputs. ... -
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OpenCLIP
An open source implementation of CLIP
...Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when trained on the same subset of YFCC. For ease of experimentation, we also provide code for training on the 3 million images in the Conceptual Captions dataset, where a ResNet-50x4 trained with our codebase reaches 22.2% top-1 ImageNet accuracy. This codebase is work in progress, and we invite all to contribute in making it more accessible and useful. ... -
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EvoTorch
Advanced evolutionary computation library built on top of PyTorch
EvoTorch is an evolutionary optimization framework built on top of PyTorch, developed by NNAISENSE. It is designed for large-scale optimization problems, particularly those that require evolutionary algorithms rather than gradient-based methods. -
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Ludwig
A codeless platform to train and test deep learning models
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest. Simple commands can be used to train models both locally and in a distributed way, and to use them to predict on new data. -
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WhisperX
Automatic Speech Recognition with Word-level Timestamps
WhisperX is an advanced speech recognition system built on top of OpenAI’s Whisper model, designed to improve transcription accuracy and timing precision for long-form audio. It addresses key limitations of standard Whisper implementations by introducing voice activity detection and forced alignment techniques to produce word-level timestamps. The system enables batched inference, significantly increasing transcription speed while maintaining high accuracy. -
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DS2API
A lightweight, high-performance full-stack middleware
DS2API is a developer tool that provides an interface for interacting programmatically with Dark Souls II game data and systems. It exposes game functionality through APIs, enabling developers to build tools, mods, or integrations on top of the game. The project focuses on reverse engineering and structuring game data into usable endpoints. It allows access to in-game entities, player states, and events for analysis or modification. The API can be used for automation, experimentation, or extending gameplay experiences. It is particularly useful for modders and developers interested in game internals. ... -
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ArrayFire
ArrayFire, a general purpose GPU library
...Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if you're interested and able to write top performing tensor functions. Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. ... -
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TNT
A lightweight library for PyTorch training tools and utilities
...This design helps separate concerns such as model training, evaluation, logging, and checkpointing, making machine learning experiments easier to manage. The framework is particularly useful for large-scale experiments where maintaining clear training workflows becomes increasingly important. Because it is built on top of PyTorch, the framework integrates naturally with existing deep learning models and datasets. -
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Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
Machine Learning for Software Engineers is an open-source learning roadmap designed to help software engineers transition into machine learning roles through a structured, practical study plan. The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a multi-month study schedule that covers topics such as machine learning fundamentals, algorithm understanding, data preparation, and practical experimentation. ... -
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NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers
NeuralPDE.jl is a Julia library for solving partial differential equations (PDEs) using physics-informed neural networks and scientific machine learning. Built on top of the SciML ecosystem, it provides a flexible and composable interface for defining PDEs and training neural networks to approximate their solutions. NeuralPDE.jl enables hybrid modeling, data-driven discovery, and fast PDE solvers in high dimensions, making it suitable for scientific research and engineering applications. -
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GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs. -
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II ElevenLabs UI
Component library and custom registry built on top of shadcn/ui
ElevenLabs UI is an open-source component library designed to accelerate the development of multimodal AI applications, particularly those involving voice agents and audio-based interactions. Built on top of modern frontend tooling such as React, Tailwind CSS, and shadcn/ui, it provides a collection of pre-built, customizable components that developers can easily integrate into their applications. The library includes specialized UI elements such as audio players, waveform visualizers, conversational interfaces, and interactive voice components, all tailored for building agent-driven experiences. ... -
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JobWinner
Curated directory of thousands of generative AI tools by category
...Entries in the collection follow a standardized format so that each listed application can be quickly compared and evaluated. AI Collection also highlights notable tools through sections such as top selections and recently added applications, helping users stay updated with emerging AI solutions. -
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EdgeChains
EdgeChains.js is Full-Stack GenAI library
...At EdgeChains, we take a unique approach to Generative AI - we think Generative AI is a deployment and configuration management challenge rather than a UI and library design pattern challenge. We build on top of a tech that has solved this problem in a different domain - Kubernetes Config Management - and bring that to Generative AI. Edgechains is built on top of jsonnet, originally built by Google based on their experience managing a vast amount of configuration code in the Borg infrastructure. -
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Infinity
Low-latency REST API for serving text-embeddings
Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers. -
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VoxCPM2
Tokenizer-Free TTS for Multilingual Speech Generation
VoxCPM2 is an advanced open-source text-to-speech system that redefines speech synthesis by eliminating traditional tokenization and instead generating continuous speech representations through a diffusion-based autoregressive architecture. Built on top of the MiniCPM model family, it enables highly natural, expressive, and context-aware speech generation that adapts tone, emotion, and pacing directly from input text. The system is trained on massive multilingual datasets, enabling support for dozens of languages and dialects while maintaining high fidelity and realism in generated audio. ... -
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SuperDuperDB
Integrate, train and manage any AI models and APIs with your database
...A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. Train models on your data in your datastore simply by querying without additional ingestion and pre-processing. -
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Qwen3-Coder
Qwen3-Coder is the code version of Qwen3
...Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models like Claude Sonnet. Qwen3-Coder supports an exceptionally long context window of 256,000 tokens, extendable to 1 million tokens using Yarn, enabling repository-scale code understanding and generation. ... -
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Wanaku
Wanaku MCP Router
Wanaku is an MCP Router designed to connect AI-enabled applications using the Model Context Protocol. Built on top of Apache Camel and Quarkus, it offers unmatched connectivity, speed, and reliability for AI agents, facilitating seamless integration across various services and platforms. -
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Evidently
Evaluate and monitor ML models from validation to production
Evidently is an open-source Python library for data scientists and ML engineers. It helps evaluate, test, and monitor ML models from validation to production. It works with tabular, text data and embeddings. -
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VOID
Video Object and Interaction Deletion
...Unlike traditional inpainting methods that only erase pixels or simple artifacts, VOID models the full interaction dynamics between objects and their environment, including shadows, reflections, and even physical consequences such as movement or balance changes. Built on top of transformer-based architectures and fine-tuned for video inpainting tasks, the system uses interaction-aware mask conditioning to ensure temporal consistency across frames. One of its most notable capabilities is its ability to simulate realistic scene behavior after object removal, such as causing an object to fall naturally if its support is removed, which significantly enhances realism.
