☁️ Build multimodal AI applications with cloud-native stack
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☁️ Build multimodal AI applications with cloud-native stack
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own
Open-source inference platform for language, vision, embedding, reranking, image, audio, and video models. Deploy with multiple engines across heterogeneous hardware, from a laptop to a distributed cluster. Serve models through OpenAI-compatible APIs.
Containers for machine learning
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Type-safe, distributed orchestration of agents, ML pipelines, and real-time inference on your k8s — in pure Python with async/await, also other languages (rust, go and ts)
A framework for efficient model inference with omni-modality models
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
A flexible, high-performance serving system for machine learning models
All-in-One Development Tool based on PaddlePaddle
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.
Dockerized OpenAI-compatible wrapper for Kokoro-82M text-to-speech w/multiplatform CPU, AMD, NVIDIA GPU PyTorch; multi-speaker, clone-tuning, caption timestamps, SSML, websockets, optional readalong web UI
Translatedcube studio is an open-source, cloud-native, one-stop machine learning / deep learning / large model AI platform. It covers the full mlops algorithm pipeline, a computing power rental platform, online notebook development, drag-and-drop task flow pipeline orchestration, multi-machine multi-GPU distributed training, hyperparameter search, inference services with VGPU virtualization, edge computing, a labeling platform with automated labeling, SFT fine-tuning / reward model / reinforcement learning training for large models such as deepseek, multi-machine large model inference with vllm/ollama/mindie, a private knowledge base, and an AI model marketplace. It supports domestic Chinese CPUs/GPUs/NPUs and the Ascend ecosystem, supports RDMA, and supports distributed frameworks such as pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/ray/volcano.
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling.
Stable diffusion for real-time music generation
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Open-source inference server and production cluster for all the models your agent needs.
🪄 Turns your machine learning code into microservices with web API, interactive GUI, and more.
cubestudio开源云原生一站式机器学习/深度学习/大模型AI平台/MaaS/mlops/人工智能平台/训推平台,算法全链路流程,多租户,算力租赁平台,token中转,拖拉拽任务流pipeline编排,多机多卡分布式训练,超参搜索,推理服务,VGPU虚拟化,云边端协同,边缘计算,自动化标注平台,deepseek等大模型sft微调/奖励模型/强化学习训练,vllm/ollama/mindie大模型多机推理,私有知识库llmops智能体,AI模型市场,支持国产异构算力调度,昇腾/寒武纪/海光/摩尔/沐曦等,支持ib/roce/RDMA,信创支持
Deep Learning Server and CLI for Torch and TensorRT