Update README.md

README.md

@@ -172,55 +172,13 @@ MODEL_TYPE='qwen2_vl'
 MODEL=AdaptLLM/food-Qwen2-VL-2B-Instruct
 
 # Set the directory for saving model prediction outputs:
-OUTPUT_DIR=./output/AdaMLLM-food-LLaVA-8B_${DOMAIN}
-
-# Run inference with data parallelism; adjust CUDA devices as needed:
-CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
-```
-
-Detailed scripts to reproduce our results:
-
-<details>
-<summary> Click to expand </summary>
-
-```bash
-# Choose from ['food', 'Recipe1M', 'Nutrition5K', 'Food101', 'FoodSeg103']
-# 'food' runs inference on all food tasks; others run on a single task
-DOMAIN='food'
-
-# 1. LLaVA-v1.6-8B
-MODEL_TYPE='llava'
-MODEL=AdaptLLM/food-LLaVA-NeXT-Llama3-8B  # HuggingFace repo ID for AdaMLLM-food-8B
-OUTPUT_DIR=./output/AdaMLLM-food-LLaVA-8B_${DOMAIN}
-
-CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
-
-# 2. Qwen2-VL-2B
-MODEL_TYPE='qwen2_vl'
-MODEL=Qwen/Qwen2-VL-2B-Instruct  # HuggingFace repo ID for Qwen2-VL
-OUTPUT_DIR=./output/Qwen2-VL-2B-Instruct_${DOMAIN}
-
-CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
-
-MODEL=AdaptLLM/food-Qwen2-VL-2B-Instruct  # HuggingFace repo ID for AdaMLLM-food-2B
 OUTPUT_DIR=./output/AdaMLLM-food-Qwen-2B_${DOMAIN}
 
-CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
-
-# 3. Llama-3.2-11B
-MODEL_TYPE='mllama'
-MODEL=meta-llama/Llama-3.2-11B-Vision-Instruct  # HuggingFace repo ID for Llama3.2
-OUTPUT_DIR=./output/Llama-3.2-11B-Vision-Instruct_${DOMAIN}
-
-CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
-
-MODEL=AdaptLLM/food-Llama-3.2-11B-Vision-Instruct  # HuggingFace repo ID for AdaMLLM-food-11B
-OUTPUT_DIR=./output/AdaMLLM-food-Llama3.2-2B_${DOMAIN}
-
+# Run inference with data parallelism; adjust CUDA devices as needed:
 CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' bash run_inference.sh ${MODEL} ${DOMAIN} ${MODEL_TYPE} ${OUTPUT_DIR} ${RESULTS_DIR}
 ```
-</details>  
 
+Detailed scripts to reproduce our results are in [Evaluation.md](https://github.com/bigai-ai/QA-Synthesizer/blob/main/docs/Evaluation.md)
 
 ### 3) Results
 The evaluation results are stored in `./eval_results`, and the model prediction outputs are in `./output`.