SGLang adds Hugging Face Transformers backend for high-throughput inference

AI Impact Summary

SGLang now offers a Hugging Face Transformers backend, enabling high-throughput, low-latency inference for transformers-compatible models. It can automatically fall back to Transformers when a model isn’t natively supported, or you can explicitly set impl='transformers' to route traffic there. This broadens access to HF Hub models (e.g., meta-llama/Llama-3.2-1B-Instruct) and custom models, reduces integration effort, and pairs with RadixAttention to improve runtime efficiency—while the team surveys ongoing performance gaps and future work on LoRA and VLM support.