diff --git a/examples/notebooks/beam-ml/run_inference_vllm.ipynb b/examples/notebooks/beam-ml/run_inference_vllm.ipynb
index e9f1e53a452..13b4a915c08 100644
--- a/examples/notebooks/beam-ml/run_inference_vllm.ipynb
+++ b/examples/notebooks/beam-ml/run_inference_vllm.ipynb
@@ -66,7 +66,7 @@
     {
       "cell_type": "markdown",
       "source": [
-        "[vLLM](https://github.com/vllm-project/vllm) is a fast and user-frienly library for LLM inference and serving. vLLM optimizes LLM inference with mechanisms like PagedAttention for memory management and continuous batching for increasing throughput. For popular models, vLLM has been shown to increase throughput by a multiple of 2 to 4. With Apache Beam, you can serve models with vLLM and scale that serving with just a few lines of code.\n",
+        "[vLLM](https://github.com/vllm-project/vllm) is a fast and user-friendly library for LLM inference and serving. vLLM optimizes LLM inference with mechanisms like PagedAttention for memory management and continuous batching for increasing throughput. For popular models, vLLM has been shown to increase throughput by a multiple of 2 to 4. With Apache Beam, you can serve models with vLLM and scale that serving with just a few lines of code.\n",
         "\n",
         "This notebook demonstrates how to run machine learning inference by using vLLM and GPUs in three ways:\n",
         "\n",