fake table for format test

content/20.results.md

@@ -77,7 +77,22 @@ The 2- and 3-bit quantisations of the 70B model show worse performance than the
 The Mixtral 8x7B model (46.7 billion parameters), a generally well-performing current open-source model, shows worse performance than all LLaMA2 models in our benchmark.
 We will update the benchmark ([https://biochatter.org/benchmark/](https://biochatter.org/benchmark/)) as new models, benchmark datasets, and BioChatter functionalities are released.
 
-**Table**
+<!-- insert table -->
+[]: # Table 1
+[]: # 
+[]: # | Model | Size | F1 score | Precision | Recall | 
+[]: # | --- | --- | --- | --- | --- |
+[]: # | OpenAI GPT-3.5-turbo | 175B | 0.92 | 0.92 | 0.92 |
+[]: # | OpenAI GPT-4 | 1.6T | 0.93 | 0.93 | 0.93 |
+[]: # | Meta LLaMA2 7B | 7B | 0.89 | 0.89 | 0.89 |
+[]: # | Meta LLaMA2 13B | 13B | 0.90 | 0.90 | 0.90 |
+[]: # | Meta LLaMA2 70B | 70B | 0.91 | 0.91 | 0.91 |
+[]: # | Meta LLaMA2 70B 2-bit | 70B | 0.88 | 0.88 | 0.88 |
+[]: # | Meta LLaMA2 70B 3-bit | 70B | 0.87 | 0.87 | 0.87 |
+[]: # | Meta LLaMA2 70B 4-bit | 70B | 0.92 | 0.92 | 0.92 |
+[]: # | Mixtral 8x7B | 46.7B | 0.86 | 0.86 | 0.86 |
+
+{#tab:benchmark}
 
 ### Knowledge Graphs