Native-speed vLLM transformers modeling backend
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The transformers vLLM backend now matches or exceeds custom vLLM implementations' speed for most LLM architectures, eliminating the need for manual porting. This means engineers can deploy any Hugging Face model with vLLM's optimized inference (continuous batching, custom kernels) by simply adding `--model-impl transformers`, cutting development time while maintaining performance.
By passing the `--model-impl transformers` flag in vLLM, you can now run Hugging Face transformers models at native-speed without waiting for custom vLLM ports or manual kernel rewrites. This backend matches or exceeds the throughput of hand-written vLLM code for dense and MoE architectures by automatically combining Hugging Face modeling with vLLM’s execution engine. For production pipelines, this eliminates the deployment lag for newly released model architectures, allowing you to ship custom or day-one models immediately at maximum serving efficiency.