# inference
**Repository Path**: kaka8899_admin/inference
## Basic Information
- **Project Name**: inference
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-01-23
- **Last Updated**: 2025-01-22
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README

# Xorbits Inference: Model Serving Made Easy π€
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English | [δΈζδ»η»](README_zh_CN.md) | [ζ₯ζ¬θͺ](README_ja_JP.md)
Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language,
speech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy
and serve your or state-of-the-art built-in models using just a single command. Whether you are a
researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full
potential of cutting-edge AI models.
## π₯ Hot Topics
### Framework Enhancements
- Support specifying worker and GPU indexes for launching models: [#1195](https://github.com/xorbitsai/inference/pull/1195)
- Support SGLang backend: [#1161](https://github.com/xorbitsai/inference/pull/1161)
- Support LoRA for LLM and image models: [#1080](https://github.com/xorbitsai/inference/pull/1080)
- Support speech recognition model: [#929](https://github.com/xorbitsai/inference/pull/929)
- Metrics support: [#906](https://github.com/xorbitsai/inference/pull/906)
- Docker image: [#855](https://github.com/xorbitsai/inference/pull/855)
- Support multimodal: [#829](https://github.com/xorbitsai/inference/pull/829)
### New Models
- Built-in support for [InternVL-Chat-V1-5](https://github.com/OpenGVLab/InternVL): [#1536](https://github.com/xorbitsai/inference/pull/1536)
- Built-in support for [Yi-1.5](https://github.com/01-ai/Yi-1.5): [#1489](https://github.com/xorbitsai/inference/pull/1489)
- Built-in support for [Llama 3](https://github.com/meta-llama/llama3): [#1332](https://github.com/xorbitsai/inference/pull/1332)
- Built-in support for [Qwen1.5 110B](https://huggingface.co/Qwen/Qwen1.5-110B-Chat): [#1388](https://github.com/xorbitsai/inference/pull/1388)
- Built-in support for [Mixtral-8x22B-instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1): [#1340](https://github.com/xorbitsai/inference/pull/1340)
- Built-in support for [Command-R](https://huggingface.co/CohereForAI/c4ai-command-r-v01): [#1310](https://github.com/xorbitsai/inference/pull/1310)
### Integrations
- [Dify](https://docs.dify.ai/advanced/model-configuration/xinference): an LLMOps platform that enables developers (and even non-developers) to quickly build useful applications based on large language models, ensuring they are visual, operable, and improvable.
- [FastGPT](https://github.com/labring/FastGPT): a knowledge-based platform built on the LLM, offers out-of-the-box data processing and model invocation capabilities, allows for workflow orchestration through Flow visualization.
- [Chatbox](https://chatboxai.app/): a desktop client for multiple cutting-edge LLM models, available on Windows, Mac and Linux.
- [RAGFlow](https://github.com/infiniflow/ragflow): is an open-source RAG engine based on deep document understanding.
## Key Features
π **Model Serving Made Easy**: Simplify the process of serving large language, speech
recognition, and multimodal models. You can set up and deploy your models
for experimentation and production with a single command.
β‘οΈ **State-of-the-Art Models**: Experiment with cutting-edge built-in models using a single
command. Inference provides access to state-of-the-art open-source models!
π₯ **Heterogeneous Hardware Utilization**: Make the most of your hardware resources with
[ggml](https://github.com/ggerganov/ggml). Xorbits Inference intelligently utilizes heterogeneous
hardware, including GPUs and CPUs, to accelerate your model inference tasks.
βοΈ **Flexible API and Interfaces**: Offer multiple interfaces for interacting
with your models, supporting OpenAI compatible RESTful API (including Function Calling API), RPC, CLI
and WebUI for seamless model management and interaction.
π **Distributed Deployment**: Excel in distributed deployment scenarios,
allowing the seamless distribution of model inference across multiple devices or machines.
π **Built-in Integration with Third-Party Libraries**: Xorbits Inference seamlessly integrates
with popular third-party libraries including [LangChain](https://python.langchain.com/docs/integrations/providers/xinference), [LlamaIndex](https://gpt-index.readthedocs.io/en/stable/examples/llm/XinferenceLocalDeployment.html#i-run-pip-install-xinference-all-in-a-terminal-window), [Dify](https://docs.dify.ai/advanced/model-configuration/xinference), and [Chatbox](https://chatboxai.app/).
## Why Xinference
| Feature | Xinference | FastChat | OpenLLM | RayLLM |
|------------------------------------------------|------------|----------|---------|--------|
| OpenAI-Compatible RESTful API | β
| β
| β
| β
|
| vLLM Integrations | β
| β
| β
| β
|
| More Inference Engines (GGML, TensorRT) | β
| β | β
| β
|
| More Platforms (CPU, Metal) | β
| β
| β | β |
| Multi-node Cluster Deployment | β
| β | β | β
|
| Image Models (Text-to-Image) | β
| β
| β | β |
| Text Embedding Models | β
| β | β | β |
| Multimodal Models | β
| β | β | β |
| Audio Models | β
| β | β | β |
| More OpenAI Functionalities (Function Calling) | β
| β | β | β |
## Getting Started
**Please give us a star before you begin, and you'll receive instant notifications for every new release on GitHub!**
* [Docs](https://inference.readthedocs.io/en/latest/index.html)
* [Built-in Models](https://inference.readthedocs.io/en/latest/models/builtin/index.html)
* [Custom Models](https://inference.readthedocs.io/en/latest/models/custom.html)
* [Deployment Docs](https://inference.readthedocs.io/en/latest/getting_started/using_xinference.html)
* [Examples and Tutorials](https://inference.readthedocs.io/en/latest/examples/index.html)
### Jupyter Notebook
The lightest way to experience Xinference is to try our [Juypter Notebook on Google Colab](https://colab.research.google.com/github/xorbitsai/inference/blob/main/examples/Xinference_Quick_Start.ipynb).
### Docker
Nvidia GPU users can start Xinference server using [Xinference Docker Image](https://inference.readthedocs.io/en/latest/getting_started/using_docker_image.html). Prior to executing the installation command, ensure that both [Docker](https://docs.docker.com/get-docker/) and [CUDA](https://developer.nvidia.com/cuda-downloads) are set up on your system.
```bash
docker run --name xinference -d -p 9997:9997 -e XINFERENCE_HOME=/data -v :/data --gpus all xprobe/xinference:latest xinference-local -H 0.0.0.0
```
### Quick Start
Install Xinference by using pip as follows. (For more options, see [Installation page](https://inference.readthedocs.io/en/latest/getting_started/installation.html).)
```bash
pip install "xinference[all]"
```
To start a local instance of Xinference, run the following command:
```bash
$ xinference-local
```
Once Xinference is running, there are multiple ways you can try it: via the web UI, via cURL,
via the command line, or via the Xinferenceβs python client. Check out our [docs]( https://inference.readthedocs.io/en/latest/getting_started/using_xinference.html#run-xinference-locally) for the guide.

## Getting involved
| Platform | Purpose |
|-----------------------------------------------------------------------------------------------|----------------------------------------------------|
| [Github Issues](https://github.com/xorbitsai/inference/issues) | Reporting bugs and filing feature requests. |
| [Slack](https://join.slack.com/t/xorbitsio/shared_invite/zt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg) | Collaborating with other Xorbits users. |
| [Twitter](https://twitter.com/xorbitsio) | Staying up-to-date on new features. |
## Contributors