Showing 16 of 16 projects
A high-throughput, memory-efficient inference and serving engine for large language models (LLMs).
High-performance C/C++ port of OpenAI's Whisper for efficient, cross-platform speech recognition.
A high-performance C/C++ port of OpenAI's Whisper model for efficient, cross-platform speech recognition.
A unified deep learning system for efficient large-scale model training and inference with advanced parallelism strategies.
Cross-platform framework for building customizable on-device machine learning pipelines for live and streaming media.
A high-performance serving framework for large language models and multimodal models, delivering low-latency and high-throughput inference.
A high-performance neural network inference framework optimized for mobile platforms, enabling efficient AI deployment on edge devices.
A fast, memory-efficient reimplementation of OpenAI's Whisper speech-to-text model using CTranslate2.
An open standard format for representing machine learning models to enable interoperability between frameworks.
An exhaustive pattern matching library for TypeScript with smart type inference and expressive API.
A low-level tensor library for machine learning with integer quantization, automatic differentiation, and zero runtime allocations.
NVIDIA's SDK for high-performance deep learning inference optimization and deployment on NVIDIA GPUs.
An open-source inference serving platform for deploying AI models from multiple frameworks across cloud, data center, and edge devices.
SDKs for adding private, on-device AI features like LLM chat, speech-to-text, and text-to-speech to mobile and web apps.
A lightweight, dependency-free JavaScript library for descriptive, regression, and inference statistics.
A deep learning framework for research, development, and production with flexible Python API and C++ core.
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