Fix OutOfMemoryError

✅ Solution

OutOfMemoryError in vllm usually stems from insufficient GPU memory to load the model or process large batches. Fix this by reducing the model size (e.g., using quantization, like AWQ), decreasing the batch size, or distributing the workload across multiple GPUs using tensor parallelism or pipeline parallelism. Consider enabling CUDA memory efficient attention or Paged Attention for better memory utilization.