Xinference: Model Serving Made Easy 🤖
Xinference is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xinference, you can effortlessly deploy and serve your state-of-the-art built-in models using just a single command. Whether you are a researcher, developer, or data scientist, Xinference empowers you to unleash the full potential of cutting-edge AI models.
Key Features
- Model Serving Made Easy: Simplify the process of serving large language, speech recognition, and multimodal models.
- State-of-the-Art Models: Experiment with cutting-edge built-in models using a single command.
- Heterogeneous Hardware Utilization: Make the most of your hardware resources with intelligent utilization of GPUs and CPUs.
- Flexible API and Interfaces: Multiple interfaces for interacting with your models, supporting OpenAI compatible RESTful API, RPC, CLI, and WebUI.
- Distributed Deployment: Seamless distribution of model inference across multiple devices or machines.
- Built-in Integration with Third-Party Libraries: Integrates with popular libraries including LangChain, LlamaIndex, Dify, and Chatbox.
Benefits
- Easy Setup: Quickly get Xinference running in your environment with starter guides and documentation.
- Cloud and Self-hosting Options: Try Xinference Cloud service or self-host the community edition.
- Enterprise Features: Additional features for organizations available upon request.
Highlights
- Jupyter Notebook Support: The lightest way to experience Xinference is through Jupyter Notebook on Google Colab.
- Docker and Kubernetes Support: Easily deploy Xinference using Docker and Kubernetes with detailed installation commands.
