Update sizes-gpu.md

Author: sozercan

articles/virtual-machines/sizes-gpu.md

@@ -21,7 +21,7 @@ GPU optimized VM sizes are specialized virtual machines available with single, m
 
 - The [NCv3-series](ncv3-series.md) and [NC T4_v3-series](nct4-v3-series.md) sizes are optimized for compute-intensive GPU-accelerated applications. Some examples are CUDA and OpenCL-based applications and simulations, AI, and Deep Learning. The NC T4 v3-series is focused on inference workloads featuring NVIDIA's Tesla T4 GPU and AMD EPYC2 Rome processor. The NCv3-series is focused on high-performance computing and AI workloads featuring NVIDIA’s Tesla V100 GPU.
 
-- The [NC 100 v4-series](nc-a100-v4-series.md) sizes are focused on midrange AI training and batch inference workload.  The NC A100 v4-series offers flexibility to select one, two, or four NVIDIA A100 80GB PCIe Tensor Core GPUs per VM to leverage the right-size GPU acceleration for your workload.
+- The [NC 100 v4-series](nc-a100-v4-series.md) sizes are focused on midrange AI training and batch inference workload. The NC A100 v4-series offers flexibility to select one, two, or four NVIDIA A100 80GB PCIe Tensor Core GPUs per VM to leverage the right-size GPU acceleration for your workload.
 
 - The [ND A100 v4-series](nda100-v4-series.md) sizes are focused on scale-up and scale-out deep learning training and accelerated HPC applications. The ND A100 v4-series uses 8 NVIDIA A100 TensorCore GPUs, each available with a 200 Gigabit Mellanox InfiniBand HDR connection and 40 GB of GPU memory.