LM Studio is described as 'Discover, download, and run local LLMs' and is a large language model (llm) tool in the ai tools & services category. There are more than 50 alternatives to LM Studio for a variety of platforms, including Mac, Windows, Linux, Android and Self-Hosted apps. The best LM Studio alternative is Ollama, which is both free and Open Source. Other great apps like LM Studio are Jan.ai, GPT4ALL, Open WebUI and AnythingLLM.
LM-Kit.NET is a versatile SDK for integrating Large Language Models (LLM) into C# applications. It provides advanced AI features like text generation, Natural Language Processing (NLP), data retrieval, content enhancement, and translation, enabling diverse industry use cases with ease.
LM-Kit Maestro is a secure, innovative desktop application that orchestrates AI agents offline, empowering you to build personalized chatbots with the advanced capabilities of LM-Kit.NET.
Gai is a beginner-friendly AI toolkit with no ads, no registration, and no other permissions required, except for Internet.
You need Ollama running on your localhost with some model. Once Ollama is running the model can be pulled from Follamac or from command line. From command line type something like: Ollama pull llama3 If you wish to pull from Follamac you can write llama3 into "Model name to...
Run LLMs on AMD Ryzen™ AI NPUs in minutes. Just like Ollama - but purpose-built and deeply optimized for the AMD NPUs.
AI00 RWKV Server is an inference API server for the RWKV language model based upon the web-rwkv inference engine.
This project aims to eliminate the barriers of using large language models by automating everything for you. All you need is a lightweight executable program of just a few megabytes. Additionally, this project provides an interface compatible with the OpenAI API, which means...
Experience the power of RWKV models directly on your device. Completely offline, privacy-first, and efficient. No internet required.
A modern web interface for managing and interacting with vLLM servers (www.github.com/vllm-project/vllm). Supports both GPU and CPU modes, with special optimizations for macOS Apple Silicon and enterprise deployment on OpenShift/Kubernetes.
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