Introduction

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.

👉 To get started, please see Quick Start!

Features

• 💡 No GPU, or Internet access is required for inference!
• 🐳 No additional tools are needed except for Docker!
• 🤏 Minimal image size, resulting in less vulnerabilities and smaller attack surface with a custom distroless-based image
• 🎵 Fine tune support
• 🚀 Easy to use declarative configuration for inference and fine tuning
• ✨ OpenAI API compatible to use with any OpenAI API compatible client
• 📸 Multi-modal model support
• 🖼️ Image generation support with Stable Diffusion
• 🦙 Support for GGUF (llama), GPTQ (exllama or exllama2), EXL2 (exllama2), and GGML (llama-ggml) and Mamba models
• 🚢 Kubernetes deployment ready
• 📦 Supports multiple models with a single image
• 🖥️ Supports GPU-accelerated inferencing with NVIDIA GPUs
• 🔐 Signed images for aikit and pre-made models
• 🌈 Support for non-proprietary and self-hosted container registries to store model images