From 389411a1d78dee5167dfe6a6da29f22be081f605 Mon Sep 17 00:00:00 2001 From: Dan McPherson Date: Sat, 3 Aug 2024 17:38:36 -0400 Subject: [PATCH] Fix typos Signed-off-by: Dan McPherson --- src/instructlab/training/main_ds.py | 2 +- src/instructlab/training/utils.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/instructlab/training/main_ds.py b/src/instructlab/training/main_ds.py index b56d5b85..fb1723d6 100644 --- a/src/instructlab/training/main_ds.py +++ b/src/instructlab/training/main_ds.py @@ -579,7 +579,7 @@ def run_training(torch_args: TorchrunArgs, train_args: TrainingArgs) -> None: DataProcessArgs( # XXX(osilkin): make a decision here, either: # 1. the CLI is fully responsible for managing where the data is written - # 2. we never cache it and simply write it to a tmp file everytime. + # 2. we never cache it and simply write it to a tmp file every time. # # An important reason for why #1 would be preferable is in the case of OpenShift/SELinux # where the user has a defined place for new temporary data to be written. diff --git a/src/instructlab/training/utils.py b/src/instructlab/training/utils.py index b68988f9..d1dcf2ae 100644 --- a/src/instructlab/training/utils.py +++ b/src/instructlab/training/utils.py @@ -689,7 +689,7 @@ def save_hf_format_ds( log_rank_0(f"saving took {time.time() - start} seconds") -# this is native deepspeed saving with optimizer, schediuler +# this is native deepspeed saving with optimizer, scheduler def save_model_ds_native( args, model,