Ollama GUI is a web interface for ollama.ai, a tool that enables running Large Language Models (LLMs) on your local machine. It provides a user-friendly platform for chatting with LLMs and accessing various models for text generation. Users can easily interact with different models, manage chat history, and explore available models through the web interface. The tool is built with Vue.js, Vite, and Tailwind CSS, offering a modern and responsive design for seamless user experience.

LlamaGPT is a self-hosted, offline, ChatGPT-like chatbot, powered by Llama 2. It is 100% private, with no data leaving your device. It supports various models, including Nous Hermes Llama 2 7B/13B/70B Chat and Code Llama 7B/13B/34B Chat. You can install LlamaGPT on your umbrelOS home server, M1/M2 Mac, or anywhere else with Docker. It also provides an OpenAI-compatible API for easy integration. LlamaGPT is still under development, with plans to add more features such as custom model loading and model switching.

Crabml is a llama.cpp compatible AI inference engine written in Rust, designed for efficient inference on various platforms with WebGPU support. It focuses on running inference tasks with SIMD acceleration and minimal memory requirements, supporting multiple models and quantization methods. The project is hackable, embeddable, and aims to provide high-performance AI inference capabilities.

The Ramalama project simplifies working with AI by utilizing OCI containers. It automatically detects GPU support, pulls necessary software in a container, and runs AI models. Users can list, pull, run, and serve models easily. The tool aims to support various GPUs and platforms in the future, making AI setup hassle-free.

Agentic is a standard AI functions/tools library optimized for TypeScript and LLM-based apps, compatible with major AI SDKs. It offers a set of thoroughly tested AI functions that can be used with favorite AI SDKs without writing glue code. The library includes various clients for services like Bing web search, calculator, Clearbit data resolution, Dexa podcast questions, and more. It also provides compound tools like SearchAndCrawl and supports multiple AI SDKs such as OpenAI, Vercel AI SDK, LangChain, LlamaIndex, Firebase Genkit, and Dexa Dexter. The goal is to create minimal clients with strongly-typed TypeScript DX, composable AIFunctions via AIFunctionSet, and compatibility with major TS AI SDKs.

MooER (摩耳) is an LLM-based speech recognition and translation model developed by Moore Threads. It allows users to transcribe speech into text (ASR) and translate speech into other languages (AST) in an end-to-end manner. The model was trained using 5K hours of data and is now also available with an 80K hours version. MooER is the first LLM-based speech model trained and inferred using domestic GPUs. The repository includes pretrained models, inference code, and a Gradio demo for a better user experience.

Ollama Operator is a Kubernetes operator designed to facilitate running large language models on Kubernetes clusters. It simplifies the process of deploying and managing multiple models on the same cluster, providing an easy-to-use interface for users. With support for various Kubernetes environments and seamless integration with Ollama models, APIs, and CLI, Ollama Operator streamlines the deployment and management of language models. By leveraging the capabilities of lama.cpp, Ollama Operator eliminates the need to worry about Python environments and CUDA drivers, making it a reliable tool for running large language models on Kubernetes.

AIKit is a one-stop shop to quickly get started to host, deploy, build and fine-tune large language models (LLMs). AIKit offers two main capabilities: Inference: AIKit uses LocalAI, which supports a wide range of inference capabilities and formats. LocalAI provides a drop-in replacement REST API that is OpenAI API compatible, so you can use any OpenAI API compatible client, such as Kubectl AI, Chatbot-UI and many more, to send requests to open-source LLMs! Fine Tuning: AIKit offers an extensible fine tuning interface. It supports Unsloth for fast, memory efficient, and easy fine-tuning experience.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

EVE is an official PyTorch implementation of Unveiling Encoder-Free Vision-Language Models. The project aims to explore the removal of vision encoders from Vision-Language Models (VLMs) and transfer LLMs to encoder-free VLMs efficiently. It also focuses on bridging the performance gap between encoder-free and encoder-based VLMs. EVE offers a superior capability with arbitrary image aspect ratio, data efficiency by utilizing publicly available data for pre-training, and training efficiency with a transparent and practical strategy for developing a pure decoder-only architecture across modalities.

DownEdit is a powerful program that allows you to download videos from various social media platforms such as TikTok, Douyin, Kuaishou, and more. With DownEdit, you can easily download videos from user profiles and edit them in bulk. You have the option to flip the videos horizontally or vertically throughout the entire directory with just a single click. Stay tuned for more exciting features coming soon!

This repository contains Refact WebUI for fine-tuning and self-hosting of code models, which can be used inside Refact plugins for code completion and chat. Users can fine-tune open-source code models, self-host them, download and upload Lloras, use models for code completion and chat inside Refact plugins, shard models, host multiple small models on one GPU, and connect GPT-models for chat using OpenAI and Anthropic keys. The repository provides a Docker container for running the self-hosted server and supports various models for completion, chat, and fine-tuning. Refact is free for individuals and small teams under the BSD-3-Clause license, with custom installation options available for GPU support. The community and support include contributing guidelines, GitHub issues for bugs, a community forum, Discord for chatting, and Twitter for product news and updates.

AirSwap Protocols is a repository containing smart contracts for developers and traders on the AirSwap peer-to-peer trading network. It includes various packages for functionalities like server registry, atomic token swap, staking, rewards pool, batch token and order calls, libraries, and utils. The repository follows a branching and release process for contracts and tools, with steps for regular development process and individual package features or patches. Users can deploy and verify contracts using specific commands with network flags.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

Gollama is a delightful tool that brings Ollama, your offline conversational AI companion, directly into your terminal. It provides a fun and interactive way to generate responses from various models without needing internet connectivity. Whether you're brainstorming ideas, exploring creative writing, or just looking for inspiration, Gollama is here to assist you. The tool offers an interactive interface, customizable prompts, multiple models selection, and visual feedback to enhance user experience. It can be installed via different methods like downloading the latest release, using Go, running with Docker, or building from source. Users can interact with Gollama through various options like specifying a custom base URL, prompt, model, and enabling raw output mode. The tool supports different modes like interactive, piped, CLI with image, and TUI with image. Gollama relies on third-party packages like bubbletea, glamour, huh, and lipgloss. The roadmap includes implementing piped mode, support for extracting codeblocks, copying responses/codeblocks to clipboard, GitHub Actions for automated releases, and downloading models directly from Ollama using the rest API. Contributions are welcome, and the project is licensed under the MIT License.

This repository contains code for the paper 'Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models'. It focuses on fine-tuning CLIP in an unsupervised manner to enhance its robustness against visual adversarial attacks. By replacing the vision encoder of large vision-language models with the fine-tuned CLIP models, it achieves state-of-the-art adversarial robustness on various vision-language tasks. The repository provides adversarially fine-tuned ViT-L/14 CLIP models and offers insights into zero-shot classification settings and clean accuracy improvements.

The WhatsApp AI Bot is a chatbot that utilizes various AI models APIs to generate responses to user input. Users can interact with the bot using commands to access different AI models such as Gemini, Gemini-Vision, CHAT-GPT, DALL-E, and Stability AI. Additionally, users have the flexibility to create their own custom models to personalize the bot's behavior. The bot operates on WhatsApp Web through Puppeteer and requires API keys for Gemini, OpenAI, and StabilityAI. It provides a range of functionalities and customization options for users interested in AI-powered chatbots.

Ollama GUI is a web interface for ollama.ai, a tool that enables running Large Language Models (LLMs) on your local machine. It provides a user-friendly platform for chatting with LLMs and accessing various models for text generation. Users can easily interact with different models, manage chat history, and explore available models through the web interface. The tool is built with Vue.js, Vite, and Tailwind CSS, offering a modern and responsive design for seamless user experience.

llmcord.py is a tool that allows users to chat with Language Model Models (LLMs) directly in Discord. It supports various LLM providers, both remote and locally hosted, and offers features like reply-based chat system, choosing any LLM, support for image and text file attachments, customizable system prompt, private access via DM, user identity awareness, streamed responses, warning messages, efficient message data caching, and asynchronous operation. The tool is designed to facilitate seamless conversations with LLMs and enhance user experience on Discord.

OpenModelDB is a community-driven database of AI upscaling models, providing a centralized platform for users to access and compare various models. The repository contains a collection of models and model metadata, facilitating easy exploration and evaluation of different AI upscaling solutions. With a focus on enhancing the accessibility and usability of AI models, OpenModelDB aims to streamline the process of finding and selecting the most suitable models for specific tasks or projects.

AI Toolkit for Visual Studio Code simplifies generative AI app development by bringing together cutting-edge AI development tools and models from Azure AI Studio Catalog and other catalogs like Hugging Face. Users can browse the AI models catalog, download them locally, fine-tune, test, and deploy them to the cloud. The toolkit offers actions such as finding supported models, testing model inference, fine-tuning models locally or remotely, and deploying fine-tuned models to the cloud. It also provides optimized AI models for Windows and a Q&A section for common issues and resolutions.

fastRAG is a research framework designed to build and explore efficient retrieval-augmented generative models. It incorporates state-of-the-art Large Language Models (LLMs) and Information Retrieval to empower researchers and developers with a comprehensive tool-set for advancing retrieval augmented generation. The framework is optimized for Intel hardware, customizable, and includes key features such as optimized RAG pipelines, efficient components, and RAG-efficient components like ColBERT and Fusion-in-Decoder (FiD). fastRAG supports various unique components and backends for running LLMs, making it a versatile tool for research and development in the field of retrieval-augmented generation.

LLM-Travel is a repository dedicated to exploring the mysteries of Large Language Models (LLM). It provides in-depth technical explanations, practical code implementations, and a platform for discussions and questions related to LLM. Join the journey to explore the fascinating world of large language models with LLM-Travel.

Transformer Explainer is an interactive visualization tool to help users learn how Transformer-based models like GPT work. It allows users to experiment with text and observe how internal components of the Transformer predict next tokens in real time. The tool runs a live GPT-2 model in the browser, providing an educational experience on text-generative models.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.