Update app.py

app.py

@@ -123,15 +123,14 @@ with gr.Blocks(theme='NoCrypt/miku') as demo:
         """)
     with gr.Tab("Memory Calculation"):
         #with gr.TabItem("Memory Calculation"):
-        with gr.Accordion("About Memory Calculation", open=False):
-            gr.Markdown("""
-            ## Memory Calculation
-        
-            Memory Calculation calculates the amount of device memory required to train or infer a model. See [Transformers Math 101](https://blog.eleuther.ai/transformer-math/) for more details on how memory overhead is calculated. 
-            Take this estimation with a grain of salt, because every implementation is different and these calculations were written to match the GPT-NeoX library as close as possible. 
-            Even for other training and inference libraries, however, we expect our script to give approximate memory estimations within acceptable error. 
-            (Please see [LLM finetuning memory requirements](https://blog.scottlogic.com/2023/11/24/llm-mem.html) for a treatment of how specific memory costs may vary framework-to-framework). Other good resources that we consulted are the [ZeRO Paper](https://arxiv.org/abs/1910.02054) and [Reducing Activation Recomputation in Large Transformer Models](https://arxiv.org/pdf/2205.05198.pdf).
-            """)
+        gr.Markdown("""
+        ## Memory Calculation
+    
+        Memory Calculation calculates the amount of device memory required to train or infer a model. See [Transformers Math 101](https://blog.eleuther.ai/transformer-math/) for more details on how memory overhead is calculated. 
+        Take this estimation with a grain of salt, because every implementation is different and these calculations were written to match the GPT-NeoX library as close as possible. 
+        Even for other training and inference libraries, however, we expect our script to give approximate memory estimations within acceptable error. 
+        (Please see [LLM finetuning memory requirements](https://blog.scottlogic.com/2023/11/24/llm-mem.html) for a treatment of how specific memory costs may vary framework-to-framework). Other good resources that we consulted are the [ZeRO Paper](https://arxiv.org/abs/1910.02054) and [Reducing Activation Recomputation in Large Transformer Models](https://arxiv.org/pdf/2205.05198.pdf).
+        """)
         with gr.Accordion("How to use it?", open=False):
             gr.Markdown("""
             ## To Use