#AI models

IOPaint is a free, open-source tool for seamless inpainting and outpainting using cutting-edge AI models. Compatible with various OS including Windows and macOS, it features object erasure, text overlay, and object replacement. Utilize plugins for super-resolution and image segmentation. Ideal for any user looking to enhance images effortlessly.

EvaDB facilitates swift construction of AI applications through its robust SQL API supporting both structured and unstructured data. It connects effortlessly with diverse data sources such as PostgreSQL and S3, leveraging pre-trained models from providers like Hugging Face, OpenAI, and YOLO for various AI tasks including image recognition and text classification. With AI-centric optimizations, EvaDB enhances query performance via caching, batching, and parallel processing, enabling developers to integrate AI into existing databases efficiently, ensuring both speed and automation without requiring extensive AI expertise.

Explore MusicGPT, a tool that uses large language models to locally generate music across multiple platforms without heavy dependencies. It supports text-based music creation with Meta's MusicGen and plans to add more models. Compatible with Mac, Linux, Windows, and Docker, it provides both UI and CLI modes, along with CUDA GPU support for faster processing. Generate quality audio samples and anticipate features like melody-based generation and endless music streaming.

OpenGPT 3.5/4 features intuitive APIs that simplify NLP integration across diverse applications, offering an accessible path for developers to implement natural language processing. This open-source project enhances application functionality and provides free access to AI models. Community collaboration and contributions are encouraged to innovate AI integration, thereby supporting seamless integration with larger systems.

The DepthAI API Demo Program offers flexibility in AI development, providing network loading, pipeline creation, and video recording capabilities. It functions as a prototyping tool with command-line and QT GUI interfaces, allowing easy testing of DepthAI features. Docker support extends usability across multiple platforms. Various AI models such as human-pose-estimation and mobilenet-ssd are supported. The program allows transformation of OAK cameras into webcams and recording of synchronized video streams. Comprehensive documentation and installation instructions facilitate ease of use. Python integration ensures seamless updates, making it an ideal tool for enhancing AI projects within an engaged development community.

ChatLuna offers a flexible AI chatbot plugin compatible with various platforms. It supports multiple output formats, such as text, voice, and image, while providing modes like chat, browse, and plugin for diverse interactions. The plugin emphasizes context awareness and long-term memory for evolving dialogue experiences and integrates Koishi's content review system. It also facilitates connecting with models like OpenAI and Google Gemini, enhancing the utility of large language models across platforms.

LeChat, inspired by KimiChat and built on UniAI, is a flexible open-source chat application featuring integration with various AI models including Moonshot, OpenAI, and Google's Gemini. While operating with limited resources, it offers substantial functionalities like office file parsing and image recognition. LeChat welcomes open-source contributions to enhance its capabilities and is optimized for easy integration with UniAI's backend framework.

Discover an interactive CLI leveraging Anthropic's Claude 3 models to streamline software development. It features intelligent code analysis, autonomous tasking, real-time search, and voice interaction within a secure virtual environment, helping manage projects and automate tasks effectively.

LitServe boosts FastAPI's capabilities, enabling AI model serving at twice the speed through features such as batching, streaming, and GPU autoscaling. It supports diverse model types, including LLMs, PyTorch, JAX, and TensorFlow, offering both self-hosting and managed deployment options. Engineered for scalable and enterprise-grade performance, LitServe facilitates the construction of compound AI systems, integrating seamlessly with vLLM for comprehensive AI model management.

Paper2GUI is an AI desktop toolbox that requires no installation to use, featuring over 50 AI models such as AI drawing, speech synthesis, and video upscaling on Windows, Mac, and Linux. It offers free apps for text-to-speech, text-to-image conversion, and video super-resolution, providing accessibility to advanced AI technology without complex setup requirements.

ONNX is a community-driven, open-source project that provides a standardized model format to support interoperability across various AI frameworks and tools. It addresses the needs of both deep learning and traditional machine learning, facilitating smooth framework transitions and aiding swift research-to-production deployment. By engaging a wide range of frameworks, tools, and hardware, ONNX enhances AI research and development. The platform invites community collaboration to continually refine its offering, fostering ongoing improvements to support the dynamic field of AI innovation efficiently.

Discover the local deployment of large language models that supports Metal, CUDA, and Vulkan. With pre-built binaries and easy source build fallback, it works without node-gyp or Python. It adapts to various hardware configurations automatically and offers CLI interaction without coding. Stay current with the latest llama.cpp releases and enable functionality like JSON schema adherence or function calling. Perfect for developers, it includes embedding capabilities, TypeScript support, and extensive documentation.

AIUI provides a voice interface for seamless interaction with GPT models in both desktop and mobile browsers. It supports natural, continuous conversation with AI and offers features like local hosting via Docker. Users can adjust language settings and choose between AI models like GPT-4 and GPT-3.5.

This advanced chat tool allows engaging with various AI models from top providers in one place. It supports multi-user and conversation management, with seamless cloud synchronization across devices, powered by Next.js and Supabase. Utilize multi-model support and personalized prompts for enhanced interactions. Keep abreast with updates such as the November 2023 enhancement for better conversation control. Join the development community through contribution guidelines and manage chat histories securely with Supabase. Interact with well-known AI models including OpenAI's GPT series and Anthropic's Claude for comprehensive conversational solutions.

Find curated resources and guides for OpenAI's ChatGPT and GPT-3 in Chinese. Access community discussions, key research papers, and enhance interactions with prompt examples. Stay updated with China's AI models and insights from global technology firms like Google and Microsoft. Explore API tools and applications to expand ChatGPT usability across platforms.

This open-source client package provides straightforward integration of OpenAI's AI models into Dart/Flutter apps, allowing developers easy access to APIs like GPT-3 and DALL-E. Streamline application development with intuitive methods that bypass HTTP request complexities, featuring functionalities such as Stream support for API completions and simple authorization processes. The library is equipped with ready-to-use snippets and benefits from regular updates and community input, supporting developers in building powerful applications efficiently.

MMDeploy is an open-source toolset aimed at efficiently deploying deep learning models. It supports over 2,300 AI models across key frameworks like ONNX, NCNN, TRT, and OpenVINO. Compatible with a wide range of hardware, it facilitates the conversion of Torch models to various formats. Designed for the OpenMMLab ecosystem, it integrates with models from multiple codebases such as mmdet, mmseg, and mmocr. The platform includes a C/C++ SDK for extensive customization and supports multiple inference backends on operating systems like Linux, Windows, macOS, and Android, optimizing deployment efficiency.

RKLLM facilitates AI model deployment on Rockchip platforms like RK3588 and RK3576, supporting various models including LLAMA and ChatGLM3-6B. With tools like RKLLM-Toolkit and Runtime, it maximizes NPU performance. Version 1.1 offers new model support and optimized processing, noted for its quantization accuracy, though not backwards compatible. Compatible with Python 3.8 and 3.10, it suits diverse environments.

Ludwig provides a low-code environment to create tailored AI models such as LLMs and neural networks with ease. The framework uses a declarative YAML-based configuration, supporting features like multi-task and multi-modality learning. Designed for scalable efficiency, it includes tools like automatic batch size selection and distributed training options like DDP and DeepSpeed. With hyperparameter tuning and model explainability, users have detailed control, along with a modular and extensible structure for different model architectures. Ready for production, Ludwig integrates Docker, supports Kubernetes with Ray, and offers model exports to Torchscript and Triton.

ModelScope is a 'Model-as-a-Service' platform that simplifies the integration and deployment of machine learning models, including those in computer vision (CV), natural language processing (NLP), and multi-modality. It provides API abstractions for easy model inference, fine-tuning, and evaluation with minimal coding. The platform includes customization options for various model components and seamless interaction with Model-Hub and Dataset-Hub. ModelScope hosts a wide range of models, accessible online, and supports modular and distributed training strategies to enrich AI development.

Explore freeGPT, an AI tool providing free access to diverse text and image generation models, such as gpt3, gpt4, and others. Easily install via pip to harness AI-generated content. This tool supports text completion and image creation, with an official Discord bot enhancing functionality. Models are sourced from multiple platforms, including you.com and pollinations.ai, ensuring consistent AI performance. The project encourages community support on GitHub. Experience smooth integration with clear examples and strong support.

DataChain enables efficient organization of unstructured data into scalable datasets, integrating seamlessly with AI models without abstraction. Features include Pythonic pipelines, multimodal data support, and metadata generation via AI models, alongside optimized operations through parallelization and vector search. Supports integration with PyTorch and TensorFlow.

Discover a curated selection of resources and tools about ChatGPT, encompassing the latest demos and applications from OpenAI. Since its launch in late 2022, this repository has been a key resource for APIs and plugin data, assisting developers and technology enthusiasts in utilizing AI. Engage with community discussions, explore practical examples, and stay updated with recent articles on ChatGPT's innovations and uses. This guide is especially beneficial for developers needing fine-tuning solutions, enterprise-level features, and multimodal functionalities, offering a comprehensive view of advanced AI models.

Utilize advanced AI models like GPT-4, DALL·E, and Whisper to enhance team efficiency. The platform supports varied deployment methods, including Serverless and Docker, ensuring reliable AI interactions and creative image generation. Benefit from cost-effective AI resource enhancement, secure SaaS, private deployments, and an intuitive admin panel for safe management. Discover features such as multi-topic dialogues, AI-powered image interpretation, and rapid data analysis to improve communication and business processes.

Prompt Poet simplifies prompt design with its user-friendly approach using YAML and Jinja2. This tool is suitable for both developers and non-technical users, enabling flexible and efficient interactions with AI models. By focusing on key features such as template-native function calling and cache-aware truncation, it enhances prompt crafting without the complex string manipulations traditionally required.

Seamless is an AI-driven multilingual and multimodal translation project that supports extensive language coverage and promotes authentic interactions. The SeamlessM4T model underpins the broader ecosystem, including SeamlessExpressive and SeamlessStreaming, allowing for real-time, expressive translations and simultaneous translation capabilities in around 100 languages. Seamless utilizes the innovative UnitY2 architecture to improve translation efficiency and reduce latency.

Argilla is a collaborative platform for AI engineers and domain experts to create high-quality datasets. It focuses on data quality to enhance model training and evaluation, allowing efficient management and iteration on AI datasets and models. Argilla is applicable in AI fields such as NLP, LLMs, and multimodal systems. This community-driven project supports open-source datasets and models, enabling organizations like the Red Cross and Prolific to enhance their AI projects.

The AIdea-server, an open-source backend developed with Golang, integrates major language and image processing models such as OpenAI's GPT, Anthropic's Claude, and Google's Gemini Pro. It supports domestic models like Tongyi Qianwen and Baichuan 53B, as well as open-source alternatives like Yi 34B and Llama2. Features include text-to-image conversion, super-resolution, and artistic QR code creation. Available for private deployment, it provides options outside of cloud services. The server's modular development is streamlined by the self-developed Glacier and Eloquent ORM frameworks.

Offers AI model integration within Neovim to enhance coding productivity and conversational capabilities. Compatible with multiple providers, including OpenAI, Google PaLM, and local models, it provides customizable programmatic prompts in Lua. Features include streaming completions, multi-provider support, and diverse chat functionalities, designed for advanced customization and integration. Ideal for developers seeking diverse AI-assisted workflows with support for both hosted and local AI models. Requires Neovim 0.9.0 or higher.

This application utilizes AI to deliver network vulnerability analysis with both CLI and GUI interfaces. Integrations with OpenAI, Bard API, and Llama enhance its capabilities. The tool supports Python, Docker, and Runpod serverless endpoints. Key features include diverse scan profiles and comprehensive assessments. Compatible with Windows and Linux, it is regularly updated for improved performance, making it valuable for security experts.

The toolkit efficiently facilitates the deployment of AI models such as object and face detection, along with segmentation. Compatible with ONNXRuntime, TensorRT, and MNN, it provides platform-wide flexibility and performance. Its simple syntax and minimal dependencies endear it to developers, further complemented by extensive model support. Being open-source ensures continuous community enhancements.

Discover an extensive array of pre-trained AI models designed for seamless multi-platform deployment using ailia SDK. The SDK offers support for various programming environments such as C++, Python, and Unity, utilizing Vulkan and Metal for GPU acceleration to deliver rapid AI inference on platforms like Windows, Mac, Linux, iOS, Android, Jetson, and Raspberry Pi. Access a broad spectrum of models for action recognition, anomaly detection, audio processing, and more, including the latest additions such as whisper-v3-turbo and florence2. Improve your AI initiatives with comprehensive tutorials available on Google Colaboratory and easy PC setup instructions.

Carefree-learn facilitates PyTorch deep learning through a module-first approach, minimizing redundant inheritance and applying dependency injection for adaptability. It focuses on user-friendly inference with simple setups and maintains backward compatibility in APIs. Future versions will include advanced training based on cutting-edge AI progressions. As an MIT-licensed solution, carefree-learn provides a straightforward method for integrating PyTorch AI models effectively.

This repository offers a vast collection of instruction tuning and learning resources, including papers and datasets, curated by PennState and OhioState experts. Focused on advancing instruction-based learning, it supports the academic community with surveys, corpora, and a collaborative environment, enhancing AI task efficiency. Explore the latest updates and contribute to improving instruction methodologies.