Efficiently serve numerous LoRA-fine-tuned LLMs on a single GPU while minimizing serving costs.
LoRAX is an inference server designed to serve thousands of LoRA fine-tuned models on one GPU, significantly reducing infrastructure expenses. It includes dynamic adapter loading from sources like HuggingFace, heterogeneous continuous batching, and adapter exchange scheduling. You can launch the LoRAX server and interact with models via its REST API, a Python client, or an OpenAI API-compatible endpoint.
Efficiently serve numerous LoRA-fine-tuned LLMs on a single GPU while minimizing serving costs.
Developers and ML engineers needing to serve a high volume of LoRA-fine-tuned LLMs on minimal GPU infrastructure.
LoRAX: Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs
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.
