LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
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☁️ Build multimodal AI applications with cloud-native stack
- neural-search
- cloud-native
- deep-learning
- machine-learning
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
- bert
- sentence-encoding
- deep-learning
- clip-model
Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own
- decision-model
- jev
- qwen3
Containers for machine learning
Production infrastructure for machine learning at scale
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)
- machine-learning
- scale
- workflow
- mlops
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
- version-control
- experiment-manager
- version
- control
Statistical Machine Intelligence & Learning Engine
- machine-learning
- regression
- clustering
- manifold-learning
All-in-One Development Tool based on PaddlePaddle
- classification
- segmentation
- deployment
- ocr
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
- knative
- machine-learning
- model-interpretability
- model-serving
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.
TranslatedOffline translation model server with low resource consumption, fast speed, and private deployment capability.
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.
- federated-learning
- deep-learning
- distributed-training
- edge-ai
A minimal Python framework for building custom AI inference servers with full control over logic, batching, and scaling.
- ai
- api
- serving
- artificial-intelligence
Hopsworks - Data-Intensive AI platform with a Feature Store
- feature-store
- aws
- azure
- data-science
A small, fast decision model, or system one model, for agentic workflows. Pick between options or rate on a scale faster than an LLM, with a calibrated confidence on every decision.
- ai
- machine-learning
- natural-language-understanding
- python
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- docker-image
- machine-learning
- machine-learning-models
- ibm