update app.py

src/app.py

@@ -7,7 +7,7 @@ import numpy as np
 import gc
 from huggingface_hub import login
 
-st.set_page_config(page_title='Can you run it? LLM version', layout="wide", initial_sidebar_state="expanded")
+st.set_page_config(page_title='Lambda LLM Calculator', layout="wide", initial_sidebar_state="expanded")
 
 model_list = [
     "mistralai/Mistral-7B-v0.1",
@@ -114,7 +114,7 @@ with col.expander("Information", expanded=True):
     where is estimated as """)
     
     st.latex(r"""\text{Memory}_\text{Inference} \approx \text{Model Size} \times 1.2""")
-    st.markdown("""- For LoRa Fine-tuning, I'm asuming a **16-bit** dtype of trainable parameters. The formula (in terms of GB) is""")
+    st.markdown("""- For LoRa Fine-tuning, This assumes a **16-bit** dtype of trainable parameters. The formula (in terms of GB) is""")
     st.latex(r"\text{Memory}_\text{LoRa} \approx \text{Model Size} + \left(\text{ \# trainable Params}_\text{Billions}\times\frac{16}{8} \times 4\right) \times 1.2")
 
 access_token = st.sidebar.text_input("Access token")