diff --git a/docs/guides/grpo-deepscaler.md b/docs/guides/grpo-deepscaler.md
index 5beddf1689..203934324f 100644
--- a/docs/guides/grpo-deepscaler.md
+++ b/docs/guides/grpo-deepscaler.md
@@ -33,7 +33,9 @@ Throughout training, the checkpoints of the model will be saved to the `results`
 
 ```sh
 uv run examples/run_eval.py \
-    generation.model_name=results/grpo-deepscaler-1.5b-8K/step_240/hf
+    generation.model_name=results/grpo-deepscaler-1.5b-8K/step_240/hf \
+    data.prompt_file=examples/prompts/cot.txt \
+    generation.vllm_cfg.max_model_len=32768
 ```
 
 Use `generation.model_name` to specify the path to the Hugging Face checkpoint. In addition, we use AIME24 as the validation dataset and calculate pass@1 on it throughout training.