Update README.md

README.md

@@ -85,13 +85,14 @@ Note: vLLM for OLMo2 32B does not correctly handle attention when the number of
 
 ### Fine-tuning
 Model fine-tuning can be done from the final checkpoint (the `main` revision of this model) or many intermediate checkpoints. Two recipes for tuning are available.
-1. Fine-tune with the OLMo repository:
+1. Fine-tune with the OLMo-core repository:
 ```bash
-python src/scripts/train/OLMo2-32B.py train_single {training_name} --trainer.load_path="{/path/to/checkpoint}" --trainer.load_strategy=if_available
+torchrun --nproc-per-node=8 ./src/scripts/official/OLMo2-0325-32B-train.py run01
 ```
-Example:
+You can override most configuration options from the command-line. For example, to override the learning rate you could launch the script like this:
+
 ```bash
-python src/scripts/train/OLMo2-32B.py train_single 32b_run_from_step_10000 --trainer.load_path="step10000" --trainer.load_strategy=if_available
+torchrun --nproc-per-node=8 ./src/scripts/train/OLMo2-0325-32B-train.py run01 --train_module.optim.lr=6e-3
 ```
 For more documentation, see the [GitHub readme](https://github.com/allenai/OLMo-core).