SmolChat-Android is a mobile application that enables users to interact with local small language models (SLMs) on-device. Users can add/remove SLMs, modify system prompts and inference parameters, create downstream tasks, and generate responses. The app uses llama.cpp for model execution, ObjectBox for database storage, and Markwon for markdown rendering. It provides a simple, extensible codebase for on-device machine learning projects.

LLM-on-Ray is a comprehensive solution for building, customizing, and deploying Large Language Models (LLMs). It simplifies complex processes into manageable steps by leveraging the power of Ray for distributed computing. The tool supports pretraining, finetuning, and serving LLMs across various hardware setups, incorporating industry and Intel optimizations for performance. It offers modular workflows with intuitive configurations, robust fault tolerance, and scalability. Additionally, it provides an Interactive Web UI for enhanced usability, including a chatbot application for testing and refining models.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

hugegraph-ai aims to explore the integration of HugeGraph with artificial intelligence (AI) and provide comprehensive support for developers to leverage HugeGraph's AI capabilities in their projects. It includes modules for large language models, graph machine learning, and a Python client for HugeGraph. The project aims to address challenges like timeliness, hallucination, and cost-related issues by integrating graph systems with AI technologies.

Sanmill is a free, powerful UCI-like N men's morris program with CUI, Flutter GUI and Qt GUI. Nine men's morris is a strategy board game for two players dating at least to the Roman Empire. The game is also known as nine-man morris , mill , mills , the mill game , merels , merrills , merelles , marelles , morelles , and ninepenny marl in English.

The LlamaEdge project makes it easy to run LLM inference apps and create OpenAI-compatible API services for the Llama2 series of LLMs locally. It provides a Rust+Wasm stack for fast, portable, and secure LLM inference on heterogeneous edge devices. The project includes source code for text generation, chatbot, and API server applications, supporting all LLMs based on the llama2 framework in the GGUF format. LlamaEdge is committed to continuously testing and validating new open-source models and offers a list of supported models with download links and startup commands. It is cross-platform, supporting various OSes, CPUs, and GPUs, and provides troubleshooting tips for common errors.

Stable Diffusion web UI is a web interface for Stable Diffusion, implemented using Gradio library. It provides a user-friendly interface to access the powerful image generation capabilities of Stable Diffusion. With Stable Diffusion web UI, users can easily generate images from text prompts, edit and refine images using inpainting and outpainting, and explore different artistic styles and techniques. The web UI also includes a range of advanced features such as textual inversion, hypernetworks, and embeddings, allowing users to customize and fine-tune the image generation process. Whether you're an artist, designer, or simply curious about the possibilities of AI-generated art, Stable Diffusion web UI is a valuable tool that empowers you to create stunning and unique images.

FunClip is an open-source, locally deployable automated video editing tool that utilizes the FunASR Paraformer series models from Alibaba DAMO Academy for speech recognition in videos. Users can select text segments or speakers from the recognition results and click the clip button to obtain the corresponding video segments. FunClip integrates advanced features such as the Paraformer-Large model for accurate Chinese ASR, SeACo-Paraformer for customized hotword recognition, CAM++ speaker recognition model, Gradio interactive interface for easy usage, support for multiple free edits with automatic SRT subtitles generation, and segment-specific SRT subtitles.

llama_deploy is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on workflows from llama_index. It allows building workflows in llama_index and deploying them seamlessly with minimal changes to code. The system includes services endlessly processing tasks, a control plane managing state and services, an orchestrator deciding task handling, and fault tolerance mechanisms. It is designed for high-concurrency scenarios, enabling real-time and high-throughput applications.

Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

AI Edge Torch is a Python library that supports converting PyTorch models into a .tflite format for on-device applications on Android, iOS, and IoT devices. It offers broad CPU coverage with initial GPU and NPU support, closely integrating with PyTorch and providing good coverage of Core ATen operators. The library includes a PyTorch converter for model conversion and a Generative API for authoring mobile-optimized PyTorch Transformer models, enabling easy deployment of Large Language Models (LLMs) on mobile devices.

Gradient CLI is a tool designed to facilitate the end-to-end MLOps process, allowing individuals and organizations to develop, train, and deploy Deep Learning models efficiently. It supports various ML/DL frameworks and provides features such as 1-click Jupyter Notebooks, scalable model training workflows, and model deployment as API endpoints. The tool can run on different infrastructures like AWS, GCP, on-premise, and Paperspace GPUs, offering automatic versioning, distributed training, hyperparameter search, and more.

ztachip is a RISCV accelerator designed for vision and AI edge applications, offering up to 20-50x acceleration compared to non-accelerated RISCV implementations. It features an innovative tensor processor hardware to accelerate various vision tasks and TensorFlow AI models. ztachip introduces a new tensor programming paradigm for massive processing/data parallelism. The repository includes technical documentation, code structure, build procedures, and reference design examples for running vision/AI applications on FPGA devices. Users can build ztachip as a standalone executable or a micropython port, and run various AI/vision applications like image classification, object detection, edge detection, motion detection, and multi-tasking on supported hardware.

FunClip is an open-source, locally deployed automated video clipping tool that leverages Alibaba TONGYI speech lab's FunASR Paraformer series models for speech recognition on videos. Users can select text segments or speakers from recognition results to obtain corresponding video clips. It integrates industrial-grade models for accurate predictions and offers hotword customization and speaker recognition features. The tool is user-friendly with Gradio interaction, supporting multi-segment clipping and providing full video and target segment subtitles. FunClip is suitable for users looking to automate video clipping tasks with advanced AI capabilities.

ChemBench is a project aimed at expanding chemistry benchmark tasks in a BIG-bench compatible way, providing a pipeline to benchmark frontier and open models. It allows users to run benchmarking tasks on models with existing presets, offering predefined parameters and processing steps. The library facilitates benchmarking models on the entire suite, addressing challenges such as prompt structure, parsing, and scoring methods. Users can contribute to the project by following the developer notes.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

SmolChat-Android is a mobile application that enables users to interact with local small language models (SLMs) on-device. Users can add/remove SLMs, modify system prompts and inference parameters, create downstream tasks, and generate responses. The app uses llama.cpp for model execution, ObjectBox for database storage, and Markwon for markdown rendering. It provides a simple, extensible codebase for on-device machine learning projects.

Spandrel is a library for loading and running pre-trained PyTorch models. It automatically detects the model architecture and hyperparameters from model files, and provides a unified interface for running models.

Wllama is a WebAssembly binding for llama.cpp, a high-performance and lightweight language model library. It enables you to run inference directly on the browser without the need for a backend or GPU. Wllama provides both high-level and low-level APIs, allowing you to perform various tasks such as completions, embeddings, tokenization, and more. It also supports model splitting, enabling you to load large models in parallel for faster download. With its Typescript support and pre-built npm package, Wllama is easy to integrate into your React Typescript projects.

lmstudio.js is a pre-release alpha client SDK for LM Studio, allowing users to use local LLMs in JS/TS/Node. It is currently undergoing rapid development with breaking changes expected. Users can follow LM Studio's announcements on Twitter and Discord. The SDK provides API usage for loading models, predicting text, setting up the local LLM server, and more. It supports features like custom loading progress tracking, model unloading, structured output prediction, and cancellation of predictions. Users can interact with LM Studio through the CLI tool 'lms' and perform tasks like text completion, conversation, and getting prediction statistics.

VisionCamera is a powerful, high-performance Camera library for React Native. It features Photo and Video capture, QR/Barcode scanner, Customizable devices and multi-cameras ("fish-eye" zoom), Customizable resolutions and aspect-ratios (4k/8k images), Customizable FPS (30..240 FPS), Frame Processors (JS worklets to run facial recognition, AI object detection, realtime video chats, ...), Smooth zooming (Reanimated), Fast pause and resume, HDR & Night modes, Custom C++/GPU accelerated video pipeline (OpenGL).

This repository contains an offline Android chat application based on llama.cpp example. Users can install, download models, and run the app completely offline and privately. To use the app, users need to go to the releases page, download and install the app. Building the app requires downloading Android Studio, cloning the repository, and importing it into Android Studio. The app can be run offline by following specific steps such as enabling developer options, wireless debugging, and downloading the stable LM model. The project is maintained by Nerve Sparks and contributions are welcome through creating feature branches and pull requests.

AIO Launcher Scripts is a collection of Lua scripts that can be used with AIO Launcher to enhance its functionality. These scripts can be used to create widget scripts, search scripts, and side menu scripts. They provide various functions such as displaying text, buttons, progress bars, charts, and interacting with app widgets. The scripts can be used to customize the appearance and behavior of the launcher, add new features, and interact with external services.

Gemini Android is a repository showcasing Google's Generative AI on Android using Stream Chat SDK for Compose. It demonstrates the Gemini API for Android, implements UI elements with Jetpack Compose, utilizes Android architecture components like Hilt and AppStartup, performs background tasks with Kotlin Coroutines, and integrates chat systems with Stream Chat Compose SDK for real-time event handling. The project also provides technical content, instructions on building the project, tech stack details, architecture overview, modularization strategies, and a contribution guideline. It follows Google's official architecture guidance and offers a real-world example of app architecture implementation.

React Native Airship is a module designed to integrate Airship's iOS and Android SDKs into React Native applications. It provides developers with the necessary tools to incorporate Airship's push notification services seamlessly. The module offers a simple and efficient way to leverage Airship's features within React Native projects, enhancing user engagement and retention through targeted notifications.

GPT Mobile is a chat assistant for Android that allows users to chat with multiple models at once. It supports various platforms such as OpenAI GPT, Anthropic Claude, and Google Gemini. Users can customize temperature, top p (Nucleus sampling), and system prompt. The app features local chat history, Material You style UI, dark mode support, and per app language setting for Android 13+. It is built using 100% Kotlin, Jetpack Compose, and follows a modern app architecture for Android developers.

This repository provides a demonstration of running a native Large Language Model (LLM) on Android devices. It supports various models such as Qwen2.5-Instruct, MiniCPM-DPO/SFT, Yuan2.0, Gemma2-it, StableLM2-Chat/Zephyr, and Phi3.5-mini-instruct. The demo models are optimized for extreme execution speed after being converted from HuggingFace or ModelScope. Users can download the demo models from the provided drive link, place them in the assets folder, and follow specific instructions for decompression and model export. The repository also includes information on quantization methods and performance benchmarks for different models on various devices.

AIDE-Plus is a comprehensive tool for Android app development, offering support for various Java syntax versions, Gradle and Maven build systems, ProGuard, AndroidX, CMake builds, APK/AAB generation, code coloring customization, data binding, and APK signing. It also provides features like AAPT2, D8, runtimeOnly, compileOnly, libgdxNatives, manifest merging, Shizuku installation support, and syntax auto-completion. The tool aims to streamline the development process and enhance the user experience by addressing common issues and providing advanced functionalities.