LoRAX supports multi-turn chat conversations combined with dynamic adapter loading through an OpenAI compatible API. Just specify any adapter as the model parameter.

LoRAX (LoRA eXchange) is a framework that allows users to serve thousands of fine-tuned models on a single GPU, dramatically reducing the cost of serving without compromising on throughput or latency.

LoRAX (LoRA eXchange) enables users to serve thousands of fine-tuned LLMs on a single GPU, dramatically reducing the cost of serving without compromising on throughput or latency. Ludwig is a declarative framework to develop, train, fine-tune, and deploy state-of-the-art deep learning and large language models.

2023年11月16日 · LoRAX (LoRA eXchange), allows users to pack 100s fine-tuned models into a single GPU and thus dramatically reduce the cost of serving. LoRAX is open-source, free to use commercially, and production-ready, with pre-built docker images and Helm charts available for immediate download and use.

LoRAX提供预构建的Docker镜像、Kubernetes Helm图表和Prometheus指标，并兼容OpenAI API，支持多轮聊天对话和私有适配器。 免费商用，采用Apache 2.0许可。 LoRAX框架支持在单个GPU上运行数千个微调模型，有效降低服务成本且不影响吞吐量和延迟。

lorax是一个创新的多lora适配器推理框架,能够在单个gpu上高效服务数千个微调模型,大幅降低服务成本,同时保持高吞吐量和低延迟。 本文深入介绍了LoRAX的核心特性、技术原理和使用方法,展示了其在大规模语言模型服务中的巨大潜力。

2024年7月18日 · LoRAX is a production ready inference server built on top of text-generation inference designed to serve one base model with many LoRA adapters. It leverages the efficiency of LoRA to handle multiple users with different LoRA adapters, dynamically loading the appropriate adapter for each request.

2023年10月18日 · LoRA Exchange (LoRAX) is a new approach to LLM serving infrastructure specifically designed for serving many fine-tuned models at once using a shared set of GPU resources. Compared with conventional dedicated LLM deployments, LoRAX consists of three novel components:

2024年2月23日 · Lorax是一款支持将多个LoRA模型热插拔到单个基础模型上的推理服务器。 这意味着在支持广泛的模型调整范围的同时，RAM内存占用会大幅减少。 划重点

2025年3月19日 · Lorax is a multi-LoRA (Low-Rank Adaptation) inference server that scales to thousands of fine-tuned Large Language Models (LLMs). It enables efficient deployment and management of numerous fine-tuned models, facilitating scalable AI applications.