ToolAI.io · Canal de GitHub
Descubre nuevos proyectos de AI de código abierto en GitHub, con información del repositorio, notas de configuración, licencias y recursos relacionados.
Datos del repositorio público
opencsgs/csghub
CSGHub is an open-source, on-premise platform for managing the full lifecycle of Large Language Model assets, including models, datasets, spaces, and code, offering functionality comparable to a private Hugging Face.
lemonade-sdk/lemonade
Lemonade is an open-source local AI server that enables users to run optimized Large Language Models (LLMs), speech, and image generation models directly on their own GPUs and NPUs, providing a free and private alternative to cloud APIs.
katanemo/plano
Plano is an AI-native proxy server and data plane built in Rust that centralizes LLM routing, agent orchestration, observability, and guardrails, allowing developers to focus on core agent logic rather than infrastructure plumbing.
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.
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.
openvinotoolkit/openvino
Open-source toolkit for optimizing and deploying AI inference across edge-to-cloud environments.
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.
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.
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.
vllm-project/vllm-ascend
A community-maintained hardware plugin that enables vLLM to run model inference and serving workloads on supported Ascend NPUs.
dstackai/dstack
A vendor-agnostic control plane for provisioning and orchestrating training, inference, development, and agentic workloads across GPU clouds, Kubernetes, and on-premises infrastructure.
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.
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