Update README.md

README.md

@@ -21,9 +21,11 @@ Single A100 was used for fine-tuning and evaluation.
 
 The [TRL](https://github.com/huggingface/trl) library was used with SFT/full-rank options:
 
+```bash
 python trl/scripts/sft.py --model_name_or_path Qwen/Qwen3-0.6B --dataset_name openai/gsm8k --dataset_config main --learning_rate 2e-5 \
 --num_train_epochs 1 --per_device_train_batch_size 2 --gradient_checkpointing --eos_token '<|im_end|>' --eval_strategy steps \
 --eval_steps 100 --completion_only_loss True --report_to wandb --output_dir /path/to/the/finetuned/model
+```
 
 The dataset was preprocessed to the conversational format:
 
@@ -47,8 +49,10 @@ dataset = dataset.map(preprocess_function)
 
 Evaluation was done with lm_eval on the test split of gsm8k:
 
-`python -m lm_eval --model vllm --model_args pretrained=${model},tensor_parallel_size=1,dtype=auto,gpu_memory_utilization=0.9,data_parallel_size=1 \
- --tasks gsm8k --batch_size 1 --apply_chat_template=True --confirm_run_unsafe_code --trust_remote_code`
+```bash
+python -m lm_eval --model vllm --model_args pretrained=${model},tensor_parallel_size=1,dtype=auto,gpu_memory_utilization=0.9,data_parallel_size=1 \
+ --tasks gsm8k --batch_size 1 --apply_chat_template=True --confirm_run_unsafe_code --trust_remote_code
+```
 
 ### Results