Update README.md

README.md

@@ -166,6 +166,9 @@ We include scripts to do this in vLLM, LMDeploy, and OpenAI (hosted for free on
 
 Install [vLLM](https://github.com/vllm-project/vllm/) using `pip install vllm`.
 
+<details>
+  <summary>Show vLLM code</summary>
+  
 ```python
 from vllm import LLM, SamplingParams
 import numpy as np
@@ -208,10 +211,18 @@ print(expected_vals)
 # [6.66570732 1.86686378 1.01102923]
 ```
 
+</details>
+
+
+
+
 ### LMDeploy
 
 Install [LMDeploy](https://github.com/InternLM/lmdeploy) using `pip install lmdeploy`.
 
+<details>
+  <summary>Show LMDeploy code</summary>
+  
 ```python
 # Un-comment this if running in a Jupyter notebook, Colab etc.
 # import nest_asyncio
@@ -266,10 +277,16 @@ print(expected_vals)
 # [6.66415229 1.84342025 1.01133205]
 ```
 
+</details>
+
+
 ### OpenAI (Hosted on Huggingface)
 
 Install [openai](https://github.com/openai/openai-python) using `pip install openai`.
 
+<details>
+  <summary>Show OpenAI + Huggingface Inference code</summary>
+  
 ```python
 from openai import OpenAI
 import numpy as np
@@ -325,6 +342,8 @@ print(expected_vals)
 # [6.64866580, 1.85144404, 1.010719508]
 ```
 
+</details>
+
 # Evaluation
 
 We perform an evaluation on 9 datasets from the [BEIR benchmark](https://github.com/beir-cellar/beir) that none of the evaluated models have been trained upon (to our knowledge).