Update README.md

README.md

@@ -81,9 +81,24 @@ blender_config = llm_blender.BlenderConfig()
 blender_config.device = "cuda" # blender ranker and fuser device
 blender = llm_blender.Blender(blender_config, ranker_config, fuser_config)
 ```
-Then you are good to use pairrankers with 
-- `blender.rank()` to rank candidates
-- `blender.compare()` to compare 2 candiates.
+
+- Then you can rank candidates with the following function
+
+```python
+inputs = ["input1", "input2"]
+candidates_texts = [["candidate1 for input1", "candidatefor input1"], ["candidate1 for input2", "candidate2 for input2"]]
+ranks = blender.rank(inputs, candidates_texts, return_scores=False, batch_size=2)
+# ranks is a list of ranks where ranks[i][j] represents the ranks of candidate-j for input-i
+```
+
+- Using pairranker to directly compare two candidates
+```python
+candidates_A = [cands[0] for cands in candidates]
+candidates_B = [cands[1] for cands in candidates]
+comparison_results = blender.compare(inputs, candidates_A, candidates_B)
+# comparison_results is a list of bool, where element[i] denotes whether candidates_A[i] is better than candidates_B[i] for inputs[i]
+```
+
 See LLM-Blender Github [README.md](https://github.com/yuchenlin/LLM-Blender#rank-and-fusion)
 and jupyter file [blender_usage.ipynb](https://github.com/yuchenlin/LLM-Blender/blob/main/blender_usage.ipynb)
 for detailed usage examples.