chore: update train_utils.py

availble -> available

src/llama_recipes/utils/train_utils.py

@@ -428,7 +428,7 @@ def setup_environ_flags(rank):
     os.environ["NCCL_ASYNC_ERROR_HANDLING"] = str(1)
     # os.environ["TORCH_DISTRIBUTED_DEBUG"] = "DETAIL"
     # This flag will help with CUDA memory fragmentations that can lead into OOM in some cases.
-    # Note this is only availble in PyTorch Nighlies (as of July 30 2023)
+    # Note this is only available in PyTorch Nighlies (as of July 30 2023)
     # os.environ['PYTORCH_CUDA_ALLOC_CONF']='expandable_segments:True'
     if rank == 0:
         print(f"--> Running with torch dist debug set to detail")