Inferencia, implementación y tiempo de ejecución

Xorbits Inference (Xinference)

xorbitsai/inference

A powerful and versatile library designed to serve language, speech recognition, and multimodal models. It allows users to swap GPT for any LLM by changing a single line of code and run models on cloud, on-prem, or locally via a unified, production-ready inference API.

★ 9,5KEstrellas
⑂ 853Bifurcaciones
60Problemas abiertos
PythonIdioma
Apache-2.0Licencia
Q@project.QualityScorePuntuación editorial

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Resumen

Xinference simplifies the deployment and serving of state-of-the-art built-in or custom AI models using a single command. It supports distributed inference across multiple devices or machines and integrates with various inference engines like vLLM and ggml. The framework provides an OpenAI-compatible RESTful API, enabling seamless migration and interoperability for applications built on the OpenAI API standard.

Características principales

  • Model Serving Made Easy: Deploy models with a single command
  • State-of-the-Art Built-in Models: Access cutting-edge open-source models effortlessly
  • Heterogeneous Hardware Utilization: Intelligently use GPUs and CPUs via ggml
  • Flexible API and Interfaces: OpenAI-compatible RESTful API, RPC, CLI, and WebUI
  • Distributed Deployment: Distribute inference across multiple devices or machines
  • Built-in Integration with Third-Party Libraries: LangChain, LlamaIndex, Dify, Chatbox, Xagent
  • Auto batching for improved throughput
  • Agent-native Serving via Xagent integration

Requisitos, instalación y guía rápida

Install via pip: `pip install "xinference[all]"`. For Docker, run: `docker run --name xinference -d -p 9997:9997 -e XINFERENCE_HOME=/data -v </on/your/host>:/data --gpus all xprobe/xinference:latest xinference-local -H 0.0.0.0`. For Kubernetes, add the helm repo: `helm repo add xinference https://xorbitsai.github.io/xinference-helm-charts` and install via helm.

Uso

Start a local instance by running: `xinference-local`. Once running, models can be interacted with via the Web UI, cURL, command line, or the Xinference Python client.

Compatibilidad de modelos y casos de uso

Supports a wide range of built-in models including Llama3, ChatGLM, GLM4, Flan-T5, Gemma, Mistral, Qwen, Whisper, WizardLM, MiniMax-M3, VibeThinker, Nex-N2, Unlimited-OCR, Ornith-1.0-35B, MiniCPM5-1B, jina-embeddings-v5, and MiniCPM-V-4.6. Also supports custom models.

Notas sobre la licencia y los riesgos

Licensed under Apache-2.0.

Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: Apache-2.0. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.

Lanzamiento y mantenimiento

Xinference 3.0.0 is available with migration notes and breaking changes. Enhancements include Agent-native Serving with Xagent, Auto batch for concurrent requests, Xllamacpp for continuous batching, distributed inference across workers, and VLLM shared KV cache across multiple replicas.

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