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6 changes: 3 additions & 3 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -358,7 +358,7 @@ The single-machine implementation starts from the [eval/main.py](eval/main.py),
For example, to run ImageNet image classification on GPUs "0", "1", and "2" on a local machine using the config [configs/eval/vitl16_in1k.yaml](configs/eval/vitl16_in1k.yaml), type the command:
```bash
python -m evals.main \
--fname configs/eval/vitl16_in1k.yaml \
--fname configs/evals/vitl16_in1k.yaml \
--devices cuda:0 cuda:1 cuda:2
```

Expand All @@ -369,15 +369,15 @@ To launch a distributed evaluation run, the implementation starts from [eval/mai
For example, to launch a distributed ImageNet image classification experiment using the config [configs/eval/vitl16_in1k.yaml](configs/eval/vitl16_in1k.yaml), type the command:
```bash
python -m evals.main_distributed \
--fname configs/eval/vitl16_in1k.yaml \
--fname configs/evals/vitl16_in1k.yaml \
--folder $path_to_save_stderr_and_stdout \
--partition $slurm_partition
```

Similarly, to launch a distributed K400 video classification experiment using the config [configs/eval/vitl16_k400.yaml](configs/eval/vitl16_k400.yaml), type the command:
```bash
python -m evals.main_distributed \
--fname configs/eval/vitl16_k400.yaml \
--fname configs/evals/vitl16_k400.yaml \
--folder $path_to_save_stderr_and_stdout \
--partition $slurm_partition
```
Expand Down