Tag

An open-source, production-ready system for serving machine-learning models at scale.

vLLM is a high-throughput, memory-efficient inference and serving engine for large language models (LLMs), built to deliver state-of-the-art performance on GPUs with features such as PagedAttention and continuous batching.

A free, open-source Python library that offers a unified API for classical machine-learning algorithms, data-pre-processing, model selection and evaluation.

Open-source high-performance framework and DSL for serving large language & vision-language models with low-latency, controllable, structured generation.

Open-source framework that accelerates fine-tuning and full training of transformer LLMs by up to 30 × while cutting VRAM requirements by roughly 90 %, letting developers train custom models quickly on commodity GPUs.

A lightweight open-source platform for running, managing, and integrating large language models locally via a simple CLI and REST API.

NVIDIA TensorRT is an SDK and tool-suite that compiles and optimizes trained neural-network models for ultra-fast, low-latency inference on NVIDIA GPUs.

Diffusers is Hugging Face’s open-source Python library that packages state-of-the-art diffusion models and tooling for fast experimentation, training, and inference across images, audio, video, and 3-D content.

fastai is an open-source deep-learning library built on PyTorch that lets developers create state-of-the-art models for computer-vision, NLP, tabular, recommendation, and time-series tasks with only a handful of lines of code.

End-to-end NVIDIA framework and micro-services platform for building, customizing, and deploying large language, speech, vision, and multimodal AI models.

XGBoost is an open-source, scalable gradient-boosting library renowned for its speed, accuracy, and support for parallel, distributed and GPU-accelerated training.

Open-source gradient-boosting library from Yandex that natively handles categorical features and offers fast CPU/GPU training.