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Inferencia, implementación y tiempo de ejecución · Proyectos de AI de código abierto en GitHub

Un índice basado en hechos de proyectos de desarrollo de LLM, agentes, MCP, RAG y AI, con licencia, configuración, descarga, capturas de pantalla y recursos relacionados para cada entrada.

Datos del repositorio público

Índice del proyecto

10 Proyectos
Captura de pantalla de Hugging Face Transformers
Inferencia, implementación y tiempo de ejecución

Hugging Face Transformers

huggingface/transformers

A model-definition framework for state-of-the-art machine learning models across text, vision, audio, and multimodal domains, supporting both inference and training.

★ 163,3K⑂ 34,1KPython
Apache-2.0Q98
Captura de pantalla de Xorbits Inference (Xinference)
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.

★ 9,5K⑂ 853Python
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

Mooncake: KVCache-Centric Infrastructure for Distributed LLM Serving

kvcache-ai/mooncake

Mooncake is a C++ infrastructure project for large-scale LLM inference and training. It separates prefill, decode, and storage resources while providing high-performance transfer, distributed KV-cache storage, and fault-tolerant expert-parallel communication.

★ 6,1K⑂ 1KC++
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

GPUStack

gpustack/gpustack

GPUStack is an open-source GPU cluster manager for serving AI models and provisioning on-demand, SSH-accessible GPU instances. It orchestrates inference engines including vLLM, SGLang, and TensorRT-LLM across on-premises, Kubernetes, and cloud environments.

★ 5,4K⑂ 604Python
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

llm-d: Distributed LLM Inference on Kubernetes

llm-d/llm-d

llm-d is an open-source serving stack that adds distributed orchestration, routing, cache management, autoscaling, and batch processing around model servers such as vLLM and SGLang. It targets high-scale production inference on Kubernetes and modern hardware accelerators.

★ 4K⑂ 649Shell
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

vLLM Ascend

vllm-project/vllm-ascend

A community-maintained hardware plugin that enables vLLM to run model inference and serving workloads on supported Ascend NPUs.

★ 2,7K⑂ 2,1KC++
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

any-llm: A Unified Python Interface for LLM Providers

mozilla-ai/any-llm

any-llm is a Python SDK for communicating with multiple LLM providers through one interface. It supports switching providers and models with minimal code changes while using official provider SDKs when available.

★ 2,2K⑂ 211Python
Apache-2.0Q98
Inferencia, implementación y tiempo de ejecución

xLLM: High-Performance Inference Engine for Diverse AI Accelerators

xllm-ai/xllm

xLLM is a C++ inference framework for LLM, VLM, DiT and REC models. It targets high-throughput, low-latency deployment on several AI accelerator families and separates service-layer scheduling and availability from engine-layer computation.

★ 1,5K⑂ 279C++
Apache-2.0Q98
Captura de pantalla de memra
Inferencia, implementación y tiempo de ejecución

memra

avifenesh/memra

A from-scratch LLM inference engine built in Rust and CUDA, specifically optimized for RTX 5090 (sm_120a) and H100 (sm_90a) architectures, delivering exactness-gated performance without relying on frameworks like ggml.

★ 312⑂ 35Rust
MITQ92
Captura de pantalla de hal0
Inferencia, implementación y tiempo de ejecución

hal0

hal0ai/hal0

An open-source, self-hosted home AI inference platform designed to turn a Linux box into an OpenAI-compatible inference appliance, with native optimization for AMD Strix Halo hardware.

★ 67⑂ 7Python
Apache-2.0Q89

Actualizado recientemente

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